{
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   "source": [
    "![Finance Toolkit](https://github.com/JerBouma/FinanceToolkit/assets/46355364/198d47bd-e1b3-492d-acc4-5d9f02d1d009)\n",
    "\n",
    "**The FinanceToolkit** is an open-source toolkit in which all relevant financial ratios (100+), indicators and performance measurements are written down in the most simplistic way allowing for complete transparency of the calculation method. This allows you to not have to rely on metrics from other providers and, given a financial statement, allow for efficient manual calculations. This leads to one uniform method of calculation being applied that is available and understood by everyone."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2937a8f2",
   "metadata": {},
   "source": [
    "# Installation\n",
    "To install the FinanceToolkit it simply requires the following:\n",
    "\n",
    "```\n",
    "pip install financetoolkit -U\n",
    "```\n",
    "\n",
    "From within Python use:\n",
    "\n",
    "```python\n",
    "from financetoolkit import Toolkit\n",
    "```\n",
    " \n",
    "To be able to get started, you need to obtain an API Key from FinancialModelingPrep. This is used to gain access to 30+ years of financial statement both annually and quarterly. Note that the Free plan is limited to 250 requests each day, 5 years of data and only features companies listed on US exchanges.\n",
    "\n",
    "___ \n",
    "\n",
    "<b><div align=\"center\">Obtain an API Key from FinancialModelingPrep <a href=\"https://www.jeroenbouma.com/fmp\" target=\"_blank\">here</a>.</div></b>\n",
    "___\n",
    "\n",
    "Through the link you are able to subscribe for the free plan and also premium plans at a **15% discount**. This is an affiliate link and thus supports the project at the same time. I have chosen FinancialModelingPrep as a source as I find it to be the most transparent, reliable and at an affordable price. When you notice that data is inaccurate or have any other issue related to the data, note that I simply provide the means to access this data and I am not responsible for the accuracy of the data itself. For this, use <a href=\"https://site.financialmodelingprep.com/contact\" target=\"_blank\">their contact form</a> or provide the data yourself. \n",
    "\n",
    "The current Notebook is revolved around the Ratios class. If you are interested in the other modules, you can find the related Notebooks below. **Please view the documentation <a href=\"https://www.jeroenbouma.com/projects/financetoolkit/docs\" target=\"_blank\">here</a> to find all the available functionality.**\n",
    "\n",
    "<style>\n",
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    "\n",
    "<div style=\"display: flex; justify-content: space-between;\" class=\"show-on-desktop\">\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//getting-started\" target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\"\">Toolkit</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//discovery-module\" target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\">Discovery</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//ratios-module\" target=\"_blank\" class=\"button button-current\" style=\"flex: 1;margin-right:5px\">Ratios</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//models-module\" target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\">Models</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//options-module\" target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\">Options</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//technicals-module\" target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\">Technicals</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//risk-module\" target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\">Risk</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//performance-module\" target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\">Performance</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//economics-module\"  target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\">Economics</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//fixed-income-module\" target=\"_blank\" class=\"button\" style=\"flex: 1;margin-right:5px\">Fixed income</a>\n",
    "    <a href=\"https://www.jeroenbouma.com/projects/financetoolkit//portfolio-module\" target=\"_blank\" class=\"button\" style=\"flex: 1; \">Portfolio</a>\n",
    "</div>"
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  {
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   "source": [
    "import pandas as pd\n",
    "\n",
    "from financetoolkit import Toolkit\n",
    "\n",
    "API_KEY = \"FINANCIAL_MODELING_PREP_API_KEY\""
   ]
  },
  {
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   "id": "a3f7fc24",
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   "source": [
    "**Initializing only is required once.** This is the case for any function so once you have obtained a balance sheet statement, it will be stored accordingly which means that requests to FinancialModelingPrep, the source used in these examples, are kept to a minimum. Note that in this example annual data is used but by adding `quarterly=True` to the Toolkit initialization, quarterly data can also be collected. Note that this requires a Premium subscription from FMP."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b3507cb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize the Toolkit with company tickers\n",
    "companies = Toolkit(\n",
    "    [\"AAPL\", \"AMZN\", \"META\", \"WMT\"], api_key=API_KEY, start_date=\"2005-01-01\"\n",
    ")"
   ]
  },
  {
   "attachments": {},
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   "id": "af12299f",
   "metadata": {},
   "source": [
    "After initialization of `Toolkit`, you can get access to the Ratios module which includes over 50 different ratios. This can be done by calling the `ratios` property. Please view the documentation <a href=\"https://www.jeroenbouma.com/projects/financetoolkit/docs/ratios\" target=\"_blank\">here</a> to find all the available ratios. \n",
    "\n",
    "Within this ratios module, the distinction is made between `collect_` and `get_`. The former obtains a collection of ratios (e.g. all solvency ratios) whereas the latter obtains a specific ratio. You will note that it will collect data first, this is done only once so that the ratios can be calculated efficiently. For example, let's start with getting all ratios."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3c79b76d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Obtaining financial statements: 100%|██████████| 3/3 [00:04<00:00,  1.42s/it]\n",
      "Obtaining historical data: 100%|██████████| 5/5 [00:00<00:00,  9.57it/s]\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
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       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>2023</th>\n",
       "      <th>2024</th>\n",
       "      <th>2025</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">AAPL</th>\n",
       "      <th>Days of Inventory Outstanding</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.7875</td>\n",
       "      <td>7.0918</td>\n",
       "      <td>7.314</td>\n",
       "      <td>6.8501</td>\n",
       "      <td>6.9509</td>\n",
       "      <td>5.175</td>\n",
       "      <td>3.2554</td>\n",
       "      <td>4.3739</td>\n",
       "      <td>6.2997</td>\n",
       "      <td>...</td>\n",
       "      <td>6.2247</td>\n",
       "      <td>9.0404</td>\n",
       "      <td>9.8195</td>\n",
       "      <td>9.0944</td>\n",
       "      <td>8.7903</td>\n",
       "      <td>9.1181</td>\n",
       "      <td>9.4097</td>\n",
       "      <td>9.6109</td>\n",
       "      <td>11.814</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>Days of Sales Outstanding</th>\n",
       "      <td>NaN</td>\n",
       "      <td>20.2862</td>\n",
       "      <td>21.9629</td>\n",
       "      <td>22.8076</td>\n",
       "      <td>24.5985</td>\n",
       "      <td>24.8211</td>\n",
       "      <td>18.3412</td>\n",
       "      <td>19.0058</td>\n",
       "      <td>25.6617</td>\n",
       "      <td>30.5127</td>\n",
       "      <td>...</td>\n",
       "      <td>27.5926</td>\n",
       "      <td>26.7723</td>\n",
       "      <td>28.2138</td>\n",
       "      <td>32.3454</td>\n",
       "      <td>25.9581</td>\n",
       "      <td>21.1517</td>\n",
       "      <td>25.2057</td>\n",
       "      <td>27.4699</td>\n",
       "      <td>29.3645</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>26.0737</td>\n",
       "      <td>29.0548</td>\n",
       "      <td>30.1216</td>\n",
       "      <td>31.4485</td>\n",
       "      <td>31.772</td>\n",
       "      <td>23.5162</td>\n",
       "      <td>22.2613</td>\n",
       "      <td>30.0356</td>\n",
       "      <td>36.8123</td>\n",
       "      <td>...</td>\n",
       "      <td>33.8174</td>\n",
       "      <td>35.8126</td>\n",
       "      <td>38.0334</td>\n",
       "      <td>41.4399</td>\n",
       "      <td>34.7484</td>\n",
       "      <td>30.2698</td>\n",
       "      <td>34.6154</td>\n",
       "      <td>37.0808</td>\n",
       "      <td>41.1785</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Days of Accounts Payable Outstanding</th>\n",
       "      <td>NaN</td>\n",
       "      <td>68.7718</td>\n",
       "      <td>96.2465</td>\n",
       "      <td>89.7359</td>\n",
       "      <td>79.0244</td>\n",
       "      <td>81.306</td>\n",
       "      <td>75.4773</td>\n",
       "      <td>74.389</td>\n",
       "      <td>74.54</td>\n",
       "      <td>85.4527</td>\n",
       "      <td>...</td>\n",
       "      <td>101.1074</td>\n",
       "      <td>105.4983</td>\n",
       "      <td>111.5912</td>\n",
       "      <td>115.2021</td>\n",
       "      <td>95.2889</td>\n",
       "      <td>83.1683</td>\n",
       "      <td>97.0504</td>\n",
       "      <td>108.0033</td>\n",
       "      <td>114.1501</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>Cash Conversion Cycle</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-42.6981</td>\n",
       "      <td>-67.1917</td>\n",
       "      <td>-59.6143</td>\n",
       "      <td>-47.5758</td>\n",
       "      <td>-49.534</td>\n",
       "      <td>-51.9611</td>\n",
       "      <td>-52.1277</td>\n",
       "      <td>-44.5044</td>\n",
       "      <td>-48.6403</td>\n",
       "      <td>...</td>\n",
       "      <td>-67.29</td>\n",
       "      <td>-69.6856</td>\n",
       "      <td>-73.5578</td>\n",
       "      <td>-73.7623</td>\n",
       "      <td>-60.5405</td>\n",
       "      <td>-52.8985</td>\n",
       "      <td>-62.435</td>\n",
       "      <td>-70.9225</td>\n",
       "      <td>-72.9716</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">WMT</th>\n",
       "      <th>EV-to-EBIT</th>\n",
       "      <td>13.293</td>\n",
       "      <td>12.3204</td>\n",
       "      <td>11.8961</td>\n",
       "      <td>12.3924</td>\n",
       "      <td>10.9359</td>\n",
       "      <td>10.3939</td>\n",
       "      <td>10.1212</td>\n",
       "      <td>11.1197</td>\n",
       "      <td>11.7127</td>\n",
       "      <td>12.7697</td>\n",
       "      <td>...</td>\n",
       "      <td>11.2081</td>\n",
       "      <td>15.7175</td>\n",
       "      <td>19.2393</td>\n",
       "      <td>30.6387</td>\n",
       "      <td>21.5795</td>\n",
       "      <td>20.4578</td>\n",
       "      <td>21.9798</td>\n",
       "      <td>25.0159</td>\n",
       "      <td>33.2665</td>\n",
       "      <td>31.1534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EV-to-EBITDA</th>\n",
       "      <td>10.4378</td>\n",
       "      <td>9.7038</td>\n",
       "      <td>8.918</td>\n",
       "      <td>9.5163</td>\n",
       "      <td>8.4082</td>\n",
       "      <td>7.8769</td>\n",
       "      <td>7.983</td>\n",
       "      <td>8.3234</td>\n",
       "      <td>8.786</td>\n",
       "      <td>9.4542</td>\n",
       "      <td>...</td>\n",
       "      <td>7.9488</td>\n",
       "      <td>10.6305</td>\n",
       "      <td>10.4329</td>\n",
       "      <td>12.4836</td>\n",
       "      <td>15.3153</td>\n",
       "      <td>13.7698</td>\n",
       "      <td>12.2649</td>\n",
       "      <td>15.5743</td>\n",
       "      <td>20.3477</td>\n",
       "      <td>20.844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EV-to-Operating-Cash-Flow</th>\n",
       "      <td>15.0593</td>\n",
       "      <td>12.8941</td>\n",
       "      <td>11.4796</td>\n",
       "      <td>13.2374</td>\n",
       "      <td>10.7294</td>\n",
       "      <td>9.3347</td>\n",
       "      <td>11.2042</td>\n",
       "      <td>11.9037</td>\n",
       "      <td>12.4633</td>\n",
       "      <td>14.5295</td>\n",
       "      <td>...</td>\n",
       "      <td>9.6818</td>\n",
       "      <td>11.0236</td>\n",
       "      <td>11.4008</td>\n",
       "      <td>14.6796</td>\n",
       "      <td>19.1357</td>\n",
       "      <td>12.8637</td>\n",
       "      <td>18.5639</td>\n",
       "      <td>16.9415</td>\n",
       "      <td>22.1355</td>\n",
       "      <td>24.206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tangible Asset Value</th>\n",
       "      <td>38593000000.0</td>\n",
       "      <td>41074000000.0</td>\n",
       "      <td>47814000000.0</td>\n",
       "      <td>48729000000.0</td>\n",
       "      <td>52216000000.0</td>\n",
       "      <td>56829000000.0</td>\n",
       "      <td>54892000000.0</td>\n",
       "      <td>55514000000.0</td>\n",
       "      <td>61760000000.0</td>\n",
       "      <td>63320000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>66916000000.0</td>\n",
       "      <td>63498000000.0</td>\n",
       "      <td>62580000000.0</td>\n",
       "      <td>48453000000.0</td>\n",
       "      <td>50479000000.0</td>\n",
       "      <td>58548000000.0</td>\n",
       "      <td>62877000000.0</td>\n",
       "      <td>55817000000.0</td>\n",
       "      <td>62458000000.0</td>\n",
       "      <td>68900000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net Current Asset Value</th>\n",
       "      <td>-4328000000.0</td>\n",
       "      <td>-5000000000.0</td>\n",
       "      <td>-5166000000.0</td>\n",
       "      <td>-10458000000.0</td>\n",
       "      <td>-6441000000.0</td>\n",
       "      <td>-7511000000.0</td>\n",
       "      <td>-6591000000.0</td>\n",
       "      <td>-7325000000.0</td>\n",
       "      <td>-11878000000.0</td>\n",
       "      <td>-8160000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-4380000000.0</td>\n",
       "      <td>-9239000000.0</td>\n",
       "      <td>-18857000000.0</td>\n",
       "      <td>-15580000000.0</td>\n",
       "      <td>-15984000000.0</td>\n",
       "      <td>-2578000000.0</td>\n",
       "      <td>-6309000000.0</td>\n",
       "      <td>-16543000000.0</td>\n",
       "      <td>-15538000000.0</td>\n",
       "      <td>-17126000000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>268 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   2005          2006  \\\n",
       "AAPL Days of Inventory Outstanding                  NaN        5.7875   \n",
       "     Days of Sales Outstanding                      NaN       20.2862   \n",
       "     Operating Cycle                                NaN       26.0737   \n",
       "     Days of Accounts Payable Outstanding           NaN       68.7718   \n",
       "     Cash Conversion Cycle                          NaN      -42.6981   \n",
       "...                                                 ...           ...   \n",
       "WMT  EV-to-EBIT                                  13.293       12.3204   \n",
       "     EV-to-EBITDA                               10.4378        9.7038   \n",
       "     EV-to-Operating-Cash-Flow                  15.0593       12.8941   \n",
       "     Tangible Asset Value                 38593000000.0 41074000000.0   \n",
       "     Net Current Asset Value              -4328000000.0 -5000000000.0   \n",
       "\n",
       "                                                   2007           2008  \\\n",
       "AAPL Days of Inventory Outstanding               7.0918          7.314   \n",
       "     Days of Sales Outstanding                  21.9629        22.8076   \n",
       "     Operating Cycle                            29.0548        30.1216   \n",
       "     Days of Accounts Payable Outstanding       96.2465        89.7359   \n",
       "     Cash Conversion Cycle                     -67.1917       -59.6143   \n",
       "...                                                 ...            ...   \n",
       "WMT  EV-to-EBIT                                 11.8961        12.3924   \n",
       "     EV-to-EBITDA                                 8.918         9.5163   \n",
       "     EV-to-Operating-Cash-Flow                  11.4796        13.2374   \n",
       "     Tangible Asset Value                 47814000000.0  48729000000.0   \n",
       "     Net Current Asset Value              -5166000000.0 -10458000000.0   \n",
       "\n",
       "                                                   2009          2010  \\\n",
       "AAPL Days of Inventory Outstanding               6.8501        6.9509   \n",
       "     Days of Sales Outstanding                  24.5985       24.8211   \n",
       "     Operating Cycle                            31.4485        31.772   \n",
       "     Days of Accounts Payable Outstanding       79.0244        81.306   \n",
       "     Cash Conversion Cycle                     -47.5758       -49.534   \n",
       "...                                                 ...           ...   \n",
       "WMT  EV-to-EBIT                                 10.9359       10.3939   \n",
       "     EV-to-EBITDA                                8.4082        7.8769   \n",
       "     EV-to-Operating-Cash-Flow                  10.7294        9.3347   \n",
       "     Tangible Asset Value                 52216000000.0 56829000000.0   \n",
       "     Net Current Asset Value              -6441000000.0 -7511000000.0   \n",
       "\n",
       "                                                   2011          2012  \\\n",
       "AAPL Days of Inventory Outstanding                5.175        3.2554   \n",
       "     Days of Sales Outstanding                  18.3412       19.0058   \n",
       "     Operating Cycle                            23.5162       22.2613   \n",
       "     Days of Accounts Payable Outstanding       75.4773        74.389   \n",
       "     Cash Conversion Cycle                     -51.9611      -52.1277   \n",
       "...                                                 ...           ...   \n",
       "WMT  EV-to-EBIT                                 10.1212       11.1197   \n",
       "     EV-to-EBITDA                                 7.983        8.3234   \n",
       "     EV-to-Operating-Cash-Flow                  11.2042       11.9037   \n",
       "     Tangible Asset Value                 54892000000.0 55514000000.0   \n",
       "     Net Current Asset Value              -6591000000.0 -7325000000.0   \n",
       "\n",
       "                                                    2013          2014  ...  \\\n",
       "AAPL Days of Inventory Outstanding                4.3739        6.2997  ...   \n",
       "     Days of Sales Outstanding                   25.6617       30.5127  ...   \n",
       "     Operating Cycle                             30.0356       36.8123  ...   \n",
       "     Days of Accounts Payable Outstanding          74.54       85.4527  ...   \n",
       "     Cash Conversion Cycle                      -44.5044      -48.6403  ...   \n",
       "...                                                  ...           ...  ...   \n",
       "WMT  EV-to-EBIT                                  11.7127       12.7697  ...   \n",
       "     EV-to-EBITDA                                  8.786        9.4542  ...   \n",
       "     EV-to-Operating-Cash-Flow                   12.4633       14.5295  ...   \n",
       "     Tangible Asset Value                  61760000000.0 63320000000.0  ...   \n",
       "     Net Current Asset Value              -11878000000.0 -8160000000.0  ...   \n",
       "\n",
       "                                                   2016          2017  \\\n",
       "AAPL Days of Inventory Outstanding               6.2247        9.0404   \n",
       "     Days of Sales Outstanding                  27.5926       26.7723   \n",
       "     Operating Cycle                            33.8174       35.8126   \n",
       "     Days of Accounts Payable Outstanding      101.1074      105.4983   \n",
       "     Cash Conversion Cycle                       -67.29      -69.6856   \n",
       "...                                                 ...           ...   \n",
       "WMT  EV-to-EBIT                                 11.2081       15.7175   \n",
       "     EV-to-EBITDA                                7.9488       10.6305   \n",
       "     EV-to-Operating-Cash-Flow                   9.6818       11.0236   \n",
       "     Tangible Asset Value                 66916000000.0 63498000000.0   \n",
       "     Net Current Asset Value              -4380000000.0 -9239000000.0   \n",
       "\n",
       "                                                    2018           2019  \\\n",
       "AAPL Days of Inventory Outstanding                9.8195         9.0944   \n",
       "     Days of Sales Outstanding                   28.2138        32.3454   \n",
       "     Operating Cycle                             38.0334        41.4399   \n",
       "     Days of Accounts Payable Outstanding       111.5912       115.2021   \n",
       "     Cash Conversion Cycle                      -73.5578       -73.7623   \n",
       "...                                                  ...            ...   \n",
       "WMT  EV-to-EBIT                                  19.2393        30.6387   \n",
       "     EV-to-EBITDA                                10.4329        12.4836   \n",
       "     EV-to-Operating-Cash-Flow                   11.4008        14.6796   \n",
       "     Tangible Asset Value                  62580000000.0  48453000000.0   \n",
       "     Net Current Asset Value              -18857000000.0 -15580000000.0   \n",
       "\n",
       "                                                    2020          2021  \\\n",
       "AAPL Days of Inventory Outstanding                8.7903        9.1181   \n",
       "     Days of Sales Outstanding                   25.9581       21.1517   \n",
       "     Operating Cycle                             34.7484       30.2698   \n",
       "     Days of Accounts Payable Outstanding        95.2889       83.1683   \n",
       "     Cash Conversion Cycle                      -60.5405      -52.8985   \n",
       "...                                                  ...           ...   \n",
       "WMT  EV-to-EBIT                                  21.5795       20.4578   \n",
       "     EV-to-EBITDA                                15.3153       13.7698   \n",
       "     EV-to-Operating-Cash-Flow                   19.1357       12.8637   \n",
       "     Tangible Asset Value                  50479000000.0 58548000000.0   \n",
       "     Net Current Asset Value              -15984000000.0 -2578000000.0   \n",
       "\n",
       "                                                   2022           2023  \\\n",
       "AAPL Days of Inventory Outstanding               9.4097         9.6109   \n",
       "     Days of Sales Outstanding                  25.2057        27.4699   \n",
       "     Operating Cycle                            34.6154        37.0808   \n",
       "     Days of Accounts Payable Outstanding       97.0504       108.0033   \n",
       "     Cash Conversion Cycle                      -62.435       -70.9225   \n",
       "...                                                 ...            ...   \n",
       "WMT  EV-to-EBIT                                 21.9798        25.0159   \n",
       "     EV-to-EBITDA                               12.2649        15.5743   \n",
       "     EV-to-Operating-Cash-Flow                  18.5639        16.9415   \n",
       "     Tangible Asset Value                 62877000000.0  55817000000.0   \n",
       "     Net Current Asset Value              -6309000000.0 -16543000000.0   \n",
       "\n",
       "                                                    2024           2025  \n",
       "AAPL Days of Inventory Outstanding                11.814            NaN  \n",
       "     Days of Sales Outstanding                   29.3645            NaN  \n",
       "     Operating Cycle                             41.1785            NaN  \n",
       "     Days of Accounts Payable Outstanding       114.1501            NaN  \n",
       "     Cash Conversion Cycle                      -72.9716            NaN  \n",
       "...                                                  ...            ...  \n",
       "WMT  EV-to-EBIT                                  33.2665        31.1534  \n",
       "     EV-to-EBITDA                                20.3477         20.844  \n",
       "     EV-to-Operating-Cash-Flow                   22.1355         24.206  \n",
       "     Tangible Asset Value                  62458000000.0  68900000000.0  \n",
       "     Net Current Asset Value              -15538000000.0 -17126000000.0  \n",
       "\n",
       "[268 rows x 21 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "companies.ratios.collect_all_ratios()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fcf7e9a",
   "metadata": {},
   "source": [
    "Given that you might not be interested in all of them, it is possible to also call each and every single one seperately."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8b9fa8b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>date</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>...</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>2023</th>\n",
       "      <th>2024</th>\n",
       "      <th>2025</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>0.2655</td>\n",
       "      <td>0.2942</td>\n",
       "      <td>0.3019</td>\n",
       "      <td>0.2989</td>\n",
       "      <td>0.3175</td>\n",
       "      <td>0.2442</td>\n",
       "      <td>0.2422</td>\n",
       "      <td>0.2516</td>\n",
       "      <td>0.2615</td>\n",
       "      <td>0.2613</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2556</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.1834</td>\n",
       "      <td>0.1594</td>\n",
       "      <td>0.1443</td>\n",
       "      <td>0.133</td>\n",
       "      <td>0.162</td>\n",
       "      <td>0.1472</td>\n",
       "      <td>0.2409</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>0.222</td>\n",
       "      <td>0.496</td>\n",
       "      <td>0.2788</td>\n",
       "      <td>0.2741</td>\n",
       "      <td>0.2179</td>\n",
       "      <td>0.2351</td>\n",
       "      <td>0.3116</td>\n",
       "      <td>0.7868</td>\n",
       "      <td>0.3701</td>\n",
       "      <td>-1.5045</td>\n",
       "      <td>...</td>\n",
       "      <td>0.3754</td>\n",
       "      <td>0.2023</td>\n",
       "      <td>0.1062</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.1183</td>\n",
       "      <td>0.1256</td>\n",
       "      <td>0.5419</td>\n",
       "      <td>0.1896</td>\n",
       "      <td>0.1352</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>META</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0222</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0984</td>\n",
       "      <td>0.3988</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.8927</td>\n",
       "      <td>0.4553</td>\n",
       "      <td>0.4012</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1838</td>\n",
       "      <td>0.2263</td>\n",
       "      <td>0.1281</td>\n",
       "      <td>0.255</td>\n",
       "      <td>0.1216</td>\n",
       "      <td>0.1674</td>\n",
       "      <td>0.195</td>\n",
       "      <td>0.1756</td>\n",
       "      <td>0.1175</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WMT</th>\n",
       "      <td>0.347</td>\n",
       "      <td>0.3309</td>\n",
       "      <td>0.3356</td>\n",
       "      <td>0.342</td>\n",
       "      <td>0.3419</td>\n",
       "      <td>0.3235</td>\n",
       "      <td>0.322</td>\n",
       "      <td>0.3256</td>\n",
       "      <td>0.3101</td>\n",
       "      <td>0.3287</td>\n",
       "      <td>...</td>\n",
       "      <td>0.3031</td>\n",
       "      <td>0.3027</td>\n",
       "      <td>0.3042</td>\n",
       "      <td>0.3736</td>\n",
       "      <td>0.2443</td>\n",
       "      <td>0.3335</td>\n",
       "      <td>0.2544</td>\n",
       "      <td>0.3364</td>\n",
       "      <td>0.2553</td>\n",
       "      <td>0.2338</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "date   2005   2006    2007   2008   2009   2010   2011   2012   2013    2014  \\\n",
       "AAPL 0.2655 0.2942  0.3019 0.2989 0.3175 0.2442 0.2422 0.2516 0.2615  0.2613   \n",
       "AMZN  0.222  0.496  0.2788 0.2741 0.2179 0.2351 0.3116 0.7868 0.3701 -1.5045   \n",
       "META    NaN    NaN -0.0222   -0.0 0.0984 0.3988   0.41 0.8927 0.4553  0.4012   \n",
       "WMT   0.347 0.3309  0.3356  0.342 0.3419 0.3235  0.322 0.3256 0.3101  0.3287   \n",
       "\n",
       "date  ...   2016   2017   2018   2019   2020   2021   2022   2023   2024  \\\n",
       "AAPL  ... 0.2556 0.2456 0.1834 0.1594 0.1443  0.133  0.162 0.1472 0.2409   \n",
       "AMZN  ... 0.3754 0.2023 0.1062   0.17 0.1183 0.1256 0.5419 0.1896 0.1352   \n",
       "META  ... 0.1838 0.2263 0.1281  0.255 0.1216 0.1674  0.195 0.1756 0.1175   \n",
       "WMT   ... 0.3031 0.3027 0.3042 0.3736 0.2443 0.3335 0.2544 0.3364 0.2553   \n",
       "\n",
       "date   2025  \n",
       "AAPL    NaN  \n",
       "AMZN    NaN  \n",
       "META    NaN  \n",
       "WMT  0.2338  \n",
       "\n",
       "[4 rows x 21 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "companies.ratios.get_effective_tax_rate()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3508a5ee",
   "metadata": {},
   "source": [
    "Some of these ratios also include optional fields depending on whether there is room for different methods of calculation. E.g. whether you'd like to have the diluted average shares included in the calculation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "70fb0e5d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
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       "      <th>2012</th>\n",
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       "      <th>2014</th>\n",
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       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
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       "      <th>2024</th>\n",
       "      <th>2025</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">AAPL</th>\n",
       "      <th>Debt-to-Assets Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>inf</td>\n",
       "      <td>0.8584</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2207</td>\n",
       "      <td>0.1394</td>\n",
       "      <td>0.0156</td>\n",
       "      <td>0.0198</td>\n",
       "      <td>0.1826</td>\n",
       "      <td>0.0302</td>\n",
       "      <td>-0.0342</td>\n",
       "      <td>-0.0642</td>\n",
       "      <td>-0.072</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debt-to-Equity Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>inf</td>\n",
       "      <td>1.3044</td>\n",
       "      <td>...</td>\n",
       "      <td>0.259</td>\n",
       "      <td>0.2717</td>\n",
       "      <td>0.2381</td>\n",
       "      <td>0.1175</td>\n",
       "      <td>0.5673</td>\n",
       "      <td>0.1563</td>\n",
       "      <td>0.2082</td>\n",
       "      <td>-0.2373</td>\n",
       "      <td>0.0483</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debt Service Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.1921</td>\n",
       "      <td>0.248</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.8474</td>\n",
       "      <td>-0.1305</td>\n",
       "      <td>0.3617</td>\n",
       "      <td>0.1864</td>\n",
       "      <td>-0.217</td>\n",
       "      <td>-0.2627</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1402</td>\n",
       "      <td>-0.199</td>\n",
       "      <td>0.0051</td>\n",
       "      <td>-0.0113</td>\n",
       "      <td>0.0402</td>\n",
       "      <td>0.3804</td>\n",
       "      <td>-0.1066</td>\n",
       "      <td>0.0141</td>\n",
       "      <td>-0.112</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity Multiplier</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.5006</td>\n",
       "      <td>0.0523</td>\n",
       "      <td>-0.0376</td>\n",
       "      <td>-0.0713</td>\n",
       "      <td>-0.0044</td>\n",
       "      <td>-0.0031</td>\n",
       "      <td>-0.0251</td>\n",
       "      <td>0.0556</td>\n",
       "      <td>0.178</td>\n",
       "      <td>...</td>\n",
       "      <td>0.093</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.1562</td>\n",
       "      <td>0.1598</td>\n",
       "      <td>0.193</td>\n",
       "      <td>0.2362</td>\n",
       "      <td>0.1772</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>-0.0363</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Free Cash Flow Yield</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.4425</td>\n",
       "      <td>0.2018</td>\n",
       "      <td>3.2557</td>\n",
       "      <td>-0.574</td>\n",
       "      <td>0.1832</td>\n",
       "      <td>0.4306</td>\n",
       "      <td>0.0361</td>\n",
       "      <td>0.0312</td>\n",
       "      <td>-0.135</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2786</td>\n",
       "      <td>-0.2996</td>\n",
       "      <td>0.4089</td>\n",
       "      <td>-0.4707</td>\n",
       "      <td>-0.265</td>\n",
       "      <td>-0.0188</td>\n",
       "      <td>0.6901</td>\n",
       "      <td>-0.3781</td>\n",
       "      <td>-0.1398</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net-Debt to EBITDA Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.2458</td>\n",
       "      <td>-0.171</td>\n",
       "      <td>-0.1137</td>\n",
       "      <td>-0.7594</td>\n",
       "      <td>0.375</td>\n",
       "      <td>-0.5247</td>\n",
       "      <td>-0.3341</td>\n",
       "      <td>-1.2636</td>\n",
       "      <td>6.3326</td>\n",
       "      <td>...</td>\n",
       "      <td>0.8015</td>\n",
       "      <td>0.4138</td>\n",
       "      <td>-0.1884</td>\n",
       "      <td>-0.285</td>\n",
       "      <td>0.4073</td>\n",
       "      <td>-0.2244</td>\n",
       "      <td>-0.0133</td>\n",
       "      <td>-0.1042</td>\n",
       "      <td>-0.1138</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash Flow Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.4653</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3976</td>\n",
       "      <td>-0.2704</td>\n",
       "      <td>0.2183</td>\n",
       "      <td>-0.0506</td>\n",
       "      <td>0.0274</td>\n",
       "      <td>0.155</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>-0.0325</td>\n",
       "      <td>0.1135</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAPEX Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.6534</td>\n",
       "      <td>0.6418</td>\n",
       "      <td>0.4426</td>\n",
       "      <td>0.0465</td>\n",
       "      <td>0.0468</td>\n",
       "      <td>-0.4256</td>\n",
       "      <td>0.0741</td>\n",
       "      <td>0.0932</td>\n",
       "      <td>0.0291</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3089</td>\n",
       "      <td>0.0268</td>\n",
       "      <td>0.1588</td>\n",
       "      <td>0.1368</td>\n",
       "      <td>0.6694</td>\n",
       "      <td>-0.1497</td>\n",
       "      <td>0.2154</td>\n",
       "      <td>-0.1158</td>\n",
       "      <td>0.241</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dividend CAPEX Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.6534</td>\n",
       "      <td>0.6418</td>\n",
       "      <td>0.4426</td>\n",
       "      <td>0.0465</td>\n",
       "      <td>0.0468</td>\n",
       "      <td>-0.4256</td>\n",
       "      <td>-0.1507</td>\n",
       "      <td>-0.3611</td>\n",
       "      <td>0.0437</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.269</td>\n",
       "      <td>-0.0252</td>\n",
       "      <td>0.1405</td>\n",
       "      <td>-0.0161</td>\n",
       "      <td>0.3378</td>\n",
       "      <td>0.0795</td>\n",
       "      <td>0.1742</td>\n",
       "      <td>-0.1102</td>\n",
       "      <td>0.1262</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">AMZN</th>\n",
       "      <th>Debt-to-Assets Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.2773</td>\n",
       "      <td>-0.2772</td>\n",
       "      <td>-0.6608</td>\n",
       "      <td>-0.7444</td>\n",
       "      <td>0.8736</td>\n",
       "      <td>0.6422</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.0969</td>\n",
       "      <td>0.776</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1667</td>\n",
       "      <td>0.5833</td>\n",
       "      <td>-0.2943</td>\n",
       "      <td>0.3768</td>\n",
       "      <td>-0.0638</td>\n",
       "      <td>0.0537</td>\n",
       "      <td>0.0939</td>\n",
       "      <td>-0.1516</td>\n",
       "      <td>-0.1845</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debt-to-Equity Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.513</td>\n",
       "      <td>-0.6132</td>\n",
       "      <td>-0.8051</td>\n",
       "      <td>-0.7838</td>\n",
       "      <td>0.9499</td>\n",
       "      <td>0.9529</td>\n",
       "      <td>1.563</td>\n",
       "      <td>0.1371</td>\n",
       "      <td>1.1872</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2551</td>\n",
       "      <td>0.7349</td>\n",
       "      <td>-0.4439</td>\n",
       "      <td>0.3381</td>\n",
       "      <td>-0.1128</td>\n",
       "      <td>-0.0682</td>\n",
       "      <td>0.1396</td>\n",
       "      <td>-0.2998</td>\n",
       "      <td>-0.3187</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debt Service Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.3248</td>\n",
       "      <td>0.1484</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>-0.1359</td>\n",
       "      <td>-0.1155</td>\n",
       "      <td>-0.573</td>\n",
       "      <td>-0.3851</td>\n",
       "      <td>-0.0899</td>\n",
       "      <td>-0.8056</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5068</td>\n",
       "      <td>-0.286</td>\n",
       "      <td>1.5614</td>\n",
       "      <td>-0.0881</td>\n",
       "      <td>0.0942</td>\n",
       "      <td>-0.0348</td>\n",
       "      <td>-0.5495</td>\n",
       "      <td>1.8363</td>\n",
       "      <td>0.7105</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity Multiplier</th>\n",
       "      <td>NaN</td>\n",
       "      <td>51.3253</td>\n",
       "      <td>-0.4402</td>\n",
       "      <td>-0.426</td>\n",
       "      <td>-0.2704</td>\n",
       "      <td>-0.0359</td>\n",
       "      <td>0.1205</td>\n",
       "      <td>0.2029</td>\n",
       "      <td>0.1179</td>\n",
       "      <td>0.1399</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0826</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>-0.0971</td>\n",
       "      <td>-0.1097</td>\n",
       "      <td>-0.043</td>\n",
       "      <td>-0.089</td>\n",
       "      <td>-0.0297</td>\n",
       "      <td>-0.0836</td>\n",
       "      <td>-0.17</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Free Cash Flow Yield</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0919</td>\n",
       "      <td>0.0404</td>\n",
       "      <td>1.0388</td>\n",
       "      <td>-0.2048</td>\n",
       "      <td>-0.3752</td>\n",
       "      <td>-0.147</td>\n",
       "      <td>-0.8652</td>\n",
       "      <td>2.0833</td>\n",
       "      <td>0.2252</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2512</td>\n",
       "      <td>-0.5682</td>\n",
       "      <td>1.0702</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>-0.3291</td>\n",
       "      <td>-1.5472</td>\n",
       "      <td>1.2644</td>\n",
       "      <td>-2.0457</td>\n",
       "      <td>-0.3058</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net-Debt to EBITDA Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.5167</td>\n",
       "      <td>-4.1695</td>\n",
       "      <td>0.4749</td>\n",
       "      <td>0.0984</td>\n",
       "      <td>-0.2499</td>\n",
       "      <td>0.2472</td>\n",
       "      <td>-0.2427</td>\n",
       "      <td>-0.4204</td>\n",
       "      <td>-0.5171</td>\n",
       "      <td>...</td>\n",
       "      <td>0.641</td>\n",
       "      <td>-4.3791</td>\n",
       "      <td>-0.9551</td>\n",
       "      <td>13.8665</td>\n",
       "      <td>0.1762</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.1749</td>\n",
       "      <td>-0.5429</td>\n",
       "      <td>-0.4098</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash Flow Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.1226</td>\n",
       "      <td>0.863</td>\n",
       "      <td>1.7769</td>\n",
       "      <td>3.5585</td>\n",
       "      <td>-0.5828</td>\n",
       "      <td>-0.4941</td>\n",
       "      <td>-0.6043</td>\n",
       "      <td>-0.0318</td>\n",
       "      <td>-0.4816</td>\n",
       "      <td>...</td>\n",
       "      <td>0.3314</td>\n",
       "      <td>-0.5718</td>\n",
       "      <td>0.9143</td>\n",
       "      <td>-0.3425</td>\n",
       "      <td>0.2847</td>\n",
       "      <td>-0.4916</td>\n",
       "      <td>-0.1616</td>\n",
       "      <td>0.8771</td>\n",
       "      <td>0.4132</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAPEX Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>0.7324</td>\n",
       "      <td>-0.5956</td>\n",
       "      <td>-0.3963</td>\n",
       "      <td>-0.4876</td>\n",
       "      <td>0.4394</td>\n",
       "      <td>-0.1204</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0136</td>\n",
       "      <td>-0.3031</td>\n",
       "      <td>0.4895</td>\n",
       "      <td>-0.0017</td>\n",
       "      <td>-0.2795</td>\n",
       "      <td>-0.5389</td>\n",
       "      <td>-0.0319</td>\n",
       "      <td>1.193</td>\n",
       "      <td>-0.1334</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dividend CAPEX Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>0.7324</td>\n",
       "      <td>-0.5956</td>\n",
       "      <td>-0.3963</td>\n",
       "      <td>-0.4876</td>\n",
       "      <td>0.4394</td>\n",
       "      <td>-0.1204</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0136</td>\n",
       "      <td>-0.3031</td>\n",
       "      <td>0.4895</td>\n",
       "      <td>-0.0017</td>\n",
       "      <td>-0.2795</td>\n",
       "      <td>-0.5389</td>\n",
       "      <td>-0.0319</td>\n",
       "      <td>1.193</td>\n",
       "      <td>-0.1334</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">META</th>\n",
       "      <th>Debt-to-Assets Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>0.7324</td>\n",
       "      <td>-1.0179</td>\n",
       "      <td>-0.3243</td>\n",
       "      <td>0.4593</td>\n",
       "      <td>-0.8295</td>\n",
       "      <td>-0.782</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>inf</td>\n",
       "      <td>4.6667</td>\n",
       "      <td>14.1765</td>\n",
       "      <td>-0.1357</td>\n",
       "      <td>0.2496</td>\n",
       "      <td>0.7129</td>\n",
       "      <td>0.1327</td>\n",
       "      <td>0.0956</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debt-to-Equity Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>0.7324</td>\n",
       "      <td>-1.0248</td>\n",
       "      <td>-0.3684</td>\n",
       "      <td>0.4501</td>\n",
       "      <td>-0.8463</td>\n",
       "      <td>-0.789</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>inf</td>\n",
       "      <td>4.9</td>\n",
       "      <td>16.322</td>\n",
       "      <td>-0.1879</td>\n",
       "      <td>0.3386</td>\n",
       "      <td>0.9037</td>\n",
       "      <td>0.1494</td>\n",
       "      <td>0.1049</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debt Service Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>0.7324</td>\n",
       "      <td>-1.3005</td>\n",
       "      <td>-0.2637</td>\n",
       "      <td>-0.7382</td>\n",
       "      <td>3.9846</td>\n",
       "      <td>0.3758</td>\n",
       "      <td>...</td>\n",
       "      <td>0.3366</td>\n",
       "      <td>0.2431</td>\n",
       "      <td>-0.3392</td>\n",
       "      <td>-0.5512</td>\n",
       "      <td>0.3686</td>\n",
       "      <td>0.0144</td>\n",
       "      <td>-0.5158</td>\n",
       "      <td>0.3658</td>\n",
       "      <td>0.4117</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity Multiplier</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>0.7324</td>\n",
       "      <td>-1.3005</td>\n",
       "      <td>-0.5024</td>\n",
       "      <td>-0.0251</td>\n",
       "      <td>-0.0583</td>\n",
       "      <td>-0.0707</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0086</td>\n",
       "      <td>0.0122</td>\n",
       "      <td>0.0252</td>\n",
       "      <td>0.0857</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>0.0068</td>\n",
       "      <td>0.0923</td>\n",
       "      <td>0.0611</td>\n",
       "      <td>0.0111</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Free Cash Flow Yield</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>-inf</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>3.75</td>\n",
       "      <td>-0.1627</td>\n",
       "      <td>...</td>\n",
       "      <td>0.6878</td>\n",
       "      <td>-0.0318</td>\n",
       "      <td>0.209</td>\n",
       "      <td>-0.1062</td>\n",
       "      <td>-0.163</td>\n",
       "      <td>0.363</td>\n",
       "      <td>0.4262</td>\n",
       "      <td>-0.1834</td>\n",
       "      <td>-0.2432</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net-Debt to EBITDA Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>-inf</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.6416</td>\n",
       "      <td>-0.9412</td>\n",
       "      <td>30.6229</td>\n",
       "      <td>-0.123</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0274</td>\n",
       "      <td>-0.4282</td>\n",
       "      <td>-0.0551</td>\n",
       "      <td>-0.0958</td>\n",
       "      <td>-0.4054</td>\n",
       "      <td>-0.715</td>\n",
       "      <td>-7.3427</td>\n",
       "      <td>-1.2524</td>\n",
       "      <td>-1.7622</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash Flow Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>-inf</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.5505</td>\n",
       "      <td>-0.701</td>\n",
       "      <td>11.9636</td>\n",
       "      <td>1.6405</td>\n",
       "      <td>...</td>\n",
       "      <td>inf</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-0.8259</td>\n",
       "      <td>-0.9399</td>\n",
       "      <td>0.034</td>\n",
       "      <td>0.1433</td>\n",
       "      <td>-0.5435</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>-0.0253</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAPEX Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>-0.0783</td>\n",
       "      <td>-0.4928</td>\n",
       "      <td>0.073</td>\n",
       "      <td>-0.4893</td>\n",
       "      <td>1.3749</td>\n",
       "      <td>-0.0386</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0524</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>-0.4151</td>\n",
       "      <td>0.143</td>\n",
       "      <td>0.0661</td>\n",
       "      <td>0.2119</td>\n",
       "      <td>-0.4831</td>\n",
       "      <td>0.6241</td>\n",
       "      <td>-0.0601</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dividend CAPEX Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0955</td>\n",
       "      <td>0.9299</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>-0.0783</td>\n",
       "      <td>-0.4928</td>\n",
       "      <td>0.073</td>\n",
       "      <td>-0.4893</td>\n",
       "      <td>1.3749</td>\n",
       "      <td>-0.0386</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0524</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>-0.4151</td>\n",
       "      <td>0.143</td>\n",
       "      <td>0.0661</td>\n",
       "      <td>0.2119</td>\n",
       "      <td>-0.4831</td>\n",
       "      <td>0.6241</td>\n",
       "      <td>-0.1727</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">WMT</th>\n",
       "      <th>Debt-to-Assets Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0848</td>\n",
       "      <td>-0.0817</td>\n",
       "      <td>0.0614</td>\n",
       "      <td>-0.0545</td>\n",
       "      <td>-0.0612</td>\n",
       "      <td>0.1373</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>-0.0351</td>\n",
       "      <td>0.0379</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017</td>\n",
       "      <td>-0.0786</td>\n",
       "      <td>-0.016</td>\n",
       "      <td>0.1641</td>\n",
       "      <td>0.1576</td>\n",
       "      <td>-0.1822</td>\n",
       "      <td>-0.0655</td>\n",
       "      <td>0.035</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>-0.0514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debt-to-Equity Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.1588</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>0.0911</td>\n",
       "      <td>-0.095</td>\n",
       "      <td>-0.0948</td>\n",
       "      <td>0.2286</td>\n",
       "      <td>0.008</td>\n",
       "      <td>-0.0619</td>\n",
       "      <td>0.0391</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0252</td>\n",
       "      <td>-0.0468</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.2669</td>\n",
       "      <td>0.2189</td>\n",
       "      <td>-0.1864</td>\n",
       "      <td>-0.1367</td>\n",
       "      <td>0.1246</td>\n",
       "      <td>-0.0349</td>\n",
       "      <td>-0.0911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Debt Service Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0432</td>\n",
       "      <td>0.0256</td>\n",
       "      <td>-0.0432</td>\n",
       "      <td>0.0944</td>\n",
       "      <td>0.0476</td>\n",
       "      <td>0.0107</td>\n",
       "      <td>-0.0218</td>\n",
       "      <td>-0.092</td>\n",
       "      <td>0.001</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1034</td>\n",
       "      <td>-0.0882</td>\n",
       "      <td>-0.2346</td>\n",
       "      <td>0.0887</td>\n",
       "      <td>-0.067</td>\n",
       "      <td>-0.0794</td>\n",
       "      <td>0.2198</td>\n",
       "      <td>-0.2536</td>\n",
       "      <td>0.319</td>\n",
       "      <td>0.0397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity Multiplier</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.2876</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>-0.0112</td>\n",
       "      <td>-0.0088</td>\n",
       "      <td>-0.0396</td>\n",
       "      <td>0.0216</td>\n",
       "      <td>0.0424</td>\n",
       "      <td>-0.0113</td>\n",
       "      <td>-0.0129</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0172</td>\n",
       "      <td>0.0209</td>\n",
       "      <td>0.0299</td>\n",
       "      <td>0.0566</td>\n",
       "      <td>0.0706</td>\n",
       "      <td>0.0227</td>\n",
       "      <td>-0.0415</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.0231</td>\n",
       "      <td>-0.0398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Free Cash Flow Yield</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4722</td>\n",
       "      <td>0.4277</td>\n",
       "      <td>0.0485</td>\n",
       "      <td>1.3235</td>\n",
       "      <td>0.2188</td>\n",
       "      <td>-0.2567</td>\n",
       "      <td>-0.0918</td>\n",
       "      <td>0.0505</td>\n",
       "      <td>-0.2448</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1244</td>\n",
       "      <td>-0.0579</td>\n",
       "      <td>-0.041</td>\n",
       "      <td>-0.2366</td>\n",
       "      <td>-0.292</td>\n",
       "      <td>0.7797</td>\n",
       "      <td>-0.5556</td>\n",
       "      <td>-0.0036</td>\n",
       "      <td>-0.2581</td>\n",
       "      <td>-0.256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net-Debt to EBITDA Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.179</td>\n",
       "      <td>-0.1329</td>\n",
       "      <td>0.1493</td>\n",
       "      <td>-0.1451</td>\n",
       "      <td>-0.0921</td>\n",
       "      <td>0.1915</td>\n",
       "      <td>0.0559</td>\n",
       "      <td>-0.0551</td>\n",
       "      <td>0.0815</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0901</td>\n",
       "      <td>-0.034</td>\n",
       "      <td>0.0786</td>\n",
       "      <td>0.2015</td>\n",
       "      <td>0.2944</td>\n",
       "      <td>-0.3233</td>\n",
       "      <td>-0.1388</td>\n",
       "      <td>0.3786</td>\n",
       "      <td>-0.1742</td>\n",
       "      <td>-0.0884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash Flow Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0603</td>\n",
       "      <td>0.1351</td>\n",
       "      <td>-0.1184</td>\n",
       "      <td>0.2035</td>\n",
       "      <td>0.1587</td>\n",
       "      <td>-0.2537</td>\n",
       "      <td>-0.0424</td>\n",
       "      <td>0.0412</td>\n",
       "      <td>-0.1314</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0328</td>\n",
       "      <td>0.252</td>\n",
       "      <td>-0.1159</td>\n",
       "      <td>-0.2156</td>\n",
       "      <td>-0.2708</td>\n",
       "      <td>0.6358</td>\n",
       "      <td>-0.2605</td>\n",
       "      <td>0.1605</td>\n",
       "      <td>0.1902</td>\n",
       "      <td>0.0405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAPEX Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0377</td>\n",
       "      <td>0.063</td>\n",
       "      <td>0.0587</td>\n",
       "      <td>0.4772</td>\n",
       "      <td>0.0702</td>\n",
       "      <td>-0.1358</td>\n",
       "      <td>-0.0357</td>\n",
       "      <td>0.1052</td>\n",
       "      <td>-0.1062</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0231</td>\n",
       "      <td>0.2425</td>\n",
       "      <td>-0.0548</td>\n",
       "      <td>-0.0483</td>\n",
       "      <td>-0.1207</td>\n",
       "      <td>0.4897</td>\n",
       "      <td>-0.475</td>\n",
       "      <td>-0.0727</td>\n",
       "      <td>0.0134</td>\n",
       "      <td>-0.1162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dividend CAPEX Coverage Ratio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0371</td>\n",
       "      <td>0.0572</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.3817</td>\n",
       "      <td>0.0541</td>\n",
       "      <td>-0.138</td>\n",
       "      <td>-0.0527</td>\n",
       "      <td>0.0724</td>\n",
       "      <td>-0.1382</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0035</td>\n",
       "      <td>0.2135</td>\n",
       "      <td>-0.0688</td>\n",
       "      <td>-0.0368</td>\n",
       "      <td>-0.1067</td>\n",
       "      <td>0.4609</td>\n",
       "      <td>-0.4299</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>0.064</td>\n",
       "      <td>-0.1047</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>36 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "date                                2005    2006    2007    2008    2009  \\\n",
       "AAPL Debt-to-Assets Ratio            NaN     NaN     NaN     NaN     NaN   \n",
       "     Debt-to-Equity Ratio            NaN     NaN     NaN     NaN     NaN   \n",
       "     Debt Service Coverage Ratio     NaN -0.1921   0.248  0.1625  0.8474   \n",
       "     Equity Multiplier               NaN  2.5006  0.0523 -0.0376 -0.0713   \n",
       "     Free Cash Flow Yield            NaN -0.4425  0.2018  3.2557  -0.574   \n",
       "     Net-Debt to EBITDA Ratio        NaN  0.2458  -0.171 -0.1137 -0.7594   \n",
       "     Cash Flow Coverage Ratio        NaN     NaN     NaN     NaN     NaN   \n",
       "     CAPEX Coverage Ratio            NaN -0.6534  0.6418  0.4426  0.0465   \n",
       "     Dividend CAPEX Coverage Ratio   NaN -0.6534  0.6418  0.4426  0.0465   \n",
       "AMZN Debt-to-Assets Ratio            NaN -0.2773 -0.2772 -0.6608 -0.7444   \n",
       "     Debt-to-Equity Ratio            NaN  -0.513 -0.6132 -0.8051 -0.7838   \n",
       "     Debt Service Coverage Ratio     NaN -0.3248  0.1484  0.0057 -0.1359   \n",
       "     Equity Multiplier               NaN 51.3253 -0.4402  -0.426 -0.2704   \n",
       "     Free Cash Flow Yield            NaN  0.0919  0.0404  1.0388 -0.2048   \n",
       "     Net-Debt to EBITDA Ratio        NaN -0.5167 -4.1695  0.4749  0.0984   \n",
       "     Cash Flow Coverage Ratio        NaN  0.1226   0.863  1.7769  3.5585   \n",
       "     CAPEX Coverage Ratio            NaN -0.0955  0.9299 -0.1875  0.7324   \n",
       "     Dividend CAPEX Coverage Ratio   NaN -0.0955  0.9299 -0.1875  0.7324   \n",
       "META Debt-to-Assets Ratio            NaN -0.0955  0.9299 -0.1875  0.7324   \n",
       "     Debt-to-Equity Ratio            NaN -0.0955  0.9299 -0.1875  0.7324   \n",
       "     Debt Service Coverage Ratio     NaN -0.0955  0.9299 -0.1875  0.7324   \n",
       "     Equity Multiplier               NaN -0.0955  0.9299 -0.1875  0.7324   \n",
       "     Free Cash Flow Yield            NaN -0.0955  0.9299 -0.1875    -inf   \n",
       "     Net-Debt to EBITDA Ratio        NaN -0.0955  0.9299 -0.1875    -inf   \n",
       "     Cash Flow Coverage Ratio        NaN -0.0955  0.9299 -0.1875    -inf   \n",
       "     CAPEX Coverage Ratio            NaN -0.0955  0.9299 -0.1875 -0.0783   \n",
       "     Dividend CAPEX Coverage Ratio   NaN -0.0955  0.9299 -0.1875 -0.0783   \n",
       "WMT  Debt-to-Assets Ratio            NaN  0.0848 -0.0817  0.0614 -0.0545   \n",
       "     Debt-to-Equity Ratio            NaN  0.1588   -0.13  0.0911  -0.095   \n",
       "     Debt Service Coverage Ratio     NaN -0.0432  0.0256 -0.0432  0.0944   \n",
       "     Equity Multiplier               NaN  5.2876  0.0026 -0.0112 -0.0088   \n",
       "     Free Cash Flow Yield            NaN  0.4722  0.4277  0.0485  1.3235   \n",
       "     Net-Debt to EBITDA Ratio        NaN   0.179 -0.1329  0.1493 -0.1451   \n",
       "     Cash Flow Coverage Ratio        NaN -0.0603  0.1351 -0.1184  0.2035   \n",
       "     CAPEX Coverage Ratio            NaN  0.0377   0.063  0.0587  0.4772   \n",
       "     Dividend CAPEX Coverage Ratio   NaN  0.0371  0.0572  0.0065  0.3817   \n",
       "\n",
       "date                                  2010    2011    2012    2013    2014  \\\n",
       "AAPL Debt-to-Assets Ratio              NaN     NaN     NaN     inf  0.8584   \n",
       "     Debt-to-Equity Ratio              NaN     NaN     NaN     inf  1.3044   \n",
       "     Debt Service Coverage Ratio   -0.1305  0.3617  0.1864  -0.217 -0.2627   \n",
       "     Equity Multiplier             -0.0044 -0.0031 -0.0251  0.0556   0.178   \n",
       "     Free Cash Flow Yield           0.1832  0.4306  0.0361  0.0312  -0.135   \n",
       "     Net-Debt to EBITDA Ratio        0.375 -0.5247 -0.3341 -1.2636  6.3326   \n",
       "     Cash Flow Coverage Ratio          NaN     NaN     NaN    -1.0 -0.4653   \n",
       "     CAPEX Coverage Ratio           0.0468 -0.4256  0.0741  0.0932  0.0291   \n",
       "     Dividend CAPEX Coverage Ratio  0.0468 -0.4256 -0.1507 -0.3611  0.0437   \n",
       "AMZN Debt-to-Assets Ratio           0.8736  0.6422     1.1  0.0969   0.776   \n",
       "     Debt-to-Equity Ratio           0.9499  0.9529   1.563  0.1371  1.1872   \n",
       "     Debt Service Coverage Ratio   -0.1155  -0.573 -0.3851 -0.0899 -0.8056   \n",
       "     Equity Multiplier             -0.0359  0.1205  0.2029  0.1179  0.1399   \n",
       "     Free Cash Flow Yield          -0.3752  -0.147 -0.8652  2.0833  0.2252   \n",
       "     Net-Debt to EBITDA Ratio      -0.2499  0.2472 -0.2427 -0.4204 -0.5171   \n",
       "     Cash Flow Coverage Ratio      -0.5828 -0.4941 -0.6043 -0.0318 -0.4816   \n",
       "     CAPEX Coverage Ratio          -0.5956 -0.3963 -0.4876  0.4394 -0.1204   \n",
       "     Dividend CAPEX Coverage Ratio -0.5956 -0.3963 -0.4876  0.4394 -0.1204   \n",
       "META Debt-to-Assets Ratio          -1.0179 -0.3243  0.4593 -0.8295  -0.782   \n",
       "     Debt-to-Equity Ratio          -1.0248 -0.3684  0.4501 -0.8463  -0.789   \n",
       "     Debt Service Coverage Ratio   -1.3005 -0.2637 -0.7382  3.9846  0.3758   \n",
       "     Equity Multiplier             -1.3005 -0.5024 -0.0251 -0.0583 -0.0707   \n",
       "     Free Cash Flow Yield              NaN     NaN    -1.0    3.75 -0.1627   \n",
       "     Net-Debt to EBITDA Ratio         -1.0 -0.6416 -0.9412 30.6229  -0.123   \n",
       "     Cash Flow Coverage Ratio         -1.0  0.5505  -0.701 11.9636  1.6405   \n",
       "     CAPEX Coverage Ratio          -0.4928   0.073 -0.4893  1.3749 -0.0386   \n",
       "     Dividend CAPEX Coverage Ratio -0.4928   0.073 -0.4893  1.3749 -0.0386   \n",
       "WMT  Debt-to-Assets Ratio          -0.0612  0.1373  0.0015 -0.0351  0.0379   \n",
       "     Debt-to-Equity Ratio          -0.0948  0.2286   0.008 -0.0619  0.0391   \n",
       "     Debt Service Coverage Ratio    0.0476  0.0107 -0.0218  -0.092   0.001   \n",
       "     Equity Multiplier             -0.0396  0.0216  0.0424 -0.0113 -0.0129   \n",
       "     Free Cash Flow Yield           0.2188 -0.2567 -0.0918  0.0505 -0.2448   \n",
       "     Net-Debt to EBITDA Ratio      -0.0921  0.1915  0.0559 -0.0551  0.0815   \n",
       "     Cash Flow Coverage Ratio       0.1587 -0.2537 -0.0424  0.0412 -0.1314   \n",
       "     CAPEX Coverage Ratio           0.0702 -0.1358 -0.0357  0.1052 -0.1062   \n",
       "     Dividend CAPEX Coverage Ratio  0.0541  -0.138 -0.0527  0.0724 -0.1382   \n",
       "\n",
       "date                                ...    2016    2017    2018    2019  \\\n",
       "AAPL Debt-to-Assets Ratio           ...  0.2207  0.1394  0.0156  0.0198   \n",
       "     Debt-to-Equity Ratio           ...   0.259  0.2717  0.2381  0.1175   \n",
       "     Debt Service Coverage Ratio    ... -0.1402  -0.199  0.0051 -0.0113   \n",
       "     Equity Multiplier              ...   0.093   0.075  0.1562  0.1598   \n",
       "     Free Cash Flow Yield           ... -0.2786 -0.2996  0.4089 -0.4707   \n",
       "     Net-Debt to EBITDA Ratio       ...  0.8015  0.4138 -0.1884  -0.285   \n",
       "     Cash Flow Coverage Ratio       ... -0.3976 -0.2704  0.2183 -0.0506   \n",
       "     CAPEX Coverage Ratio           ... -0.3089  0.0268  0.1588  0.1368   \n",
       "     Dividend CAPEX Coverage Ratio  ...  -0.269 -0.0252  0.1405 -0.0161   \n",
       "AMZN Debt-to-Assets Ratio           ... -0.1667  0.5833 -0.2943  0.3768   \n",
       "     Debt-to-Equity Ratio           ... -0.2551  0.7349 -0.4439  0.3381   \n",
       "     Debt Service Coverage Ratio    ...  0.5068  -0.286  1.5614 -0.0881   \n",
       "     Equity Multiplier              ... -0.0826  0.0075 -0.0971 -0.1097   \n",
       "     Free Cash Flow Yield           ...  0.2512 -0.5682  1.0702  0.0042   \n",
       "     Net-Debt to EBITDA Ratio       ...   0.641 -4.3791 -0.9551 13.8665   \n",
       "     Cash Flow Coverage Ratio       ...  0.3314 -0.5718  0.9143 -0.3425   \n",
       "     CAPEX Coverage Ratio           ... -0.0136 -0.3031  0.4895 -0.0017   \n",
       "     Dividend CAPEX Coverage Ratio  ... -0.0136 -0.3031  0.4895 -0.0017   \n",
       "META Debt-to-Assets Ratio           ...    -1.0     inf  4.6667 14.1765   \n",
       "     Debt-to-Equity Ratio           ...    -1.0     inf     4.9  16.322   \n",
       "     Debt Service Coverage Ratio    ...  0.3366  0.2431 -0.3392 -0.5512   \n",
       "     Equity Multiplier              ... -0.0086  0.0122  0.0252  0.0857   \n",
       "     Free Cash Flow Yield           ...  0.6878 -0.0318   0.209 -0.1062   \n",
       "     Net-Debt to EBITDA Ratio       ...  0.0274 -0.4282 -0.0551 -0.0958   \n",
       "     Cash Flow Coverage Ratio       ...     inf    -1.0 -0.8259 -0.9399   \n",
       "     CAPEX Coverage Ratio           ...  0.0524  0.0028 -0.4151   0.143   \n",
       "     Dividend CAPEX Coverage Ratio  ...  0.0524  0.0028 -0.4151   0.143   \n",
       "WMT  Debt-to-Assets Ratio           ...   0.017 -0.0786  -0.016  0.1641   \n",
       "     Debt-to-Equity Ratio           ...  0.0252 -0.0468  0.0084  0.2669   \n",
       "     Debt Service Coverage Ratio    ... -0.1034 -0.0882 -0.2346  0.0887   \n",
       "     Equity Multiplier              ... -0.0172  0.0209  0.0299  0.0566   \n",
       "     Free Cash Flow Yield           ... -0.1244 -0.0579  -0.041 -0.2366   \n",
       "     Net-Debt to EBITDA Ratio       ...  0.0901  -0.034  0.0786  0.2015   \n",
       "     Cash Flow Coverage Ratio       ... -0.0328   0.252 -0.1159 -0.2156   \n",
       "     CAPEX Coverage Ratio           ...  0.0231  0.2425 -0.0548 -0.0483   \n",
       "     Dividend CAPEX Coverage Ratio  ... -0.0035  0.2135 -0.0688 -0.0368   \n",
       "\n",
       "date                                  2020    2021    2022    2023    2024  \\\n",
       "AAPL Debt-to-Assets Ratio           0.1826  0.0302 -0.0342 -0.0642  -0.072   \n",
       "     Debt-to-Equity Ratio           0.5673  0.1563  0.2082 -0.2373  0.0483   \n",
       "     Debt Service Coverage Ratio    0.0402  0.3804 -0.1066  0.0141  -0.112   \n",
       "     Equity Multiplier               0.193  0.2362  0.1772  0.0106 -0.0363   \n",
       "     Free Cash Flow Yield           -0.265 -0.0188  0.6901 -0.3781 -0.1398   \n",
       "     Net-Debt to EBITDA Ratio       0.4073 -0.2244 -0.0133 -0.1042 -0.1138   \n",
       "     Cash Flow Coverage Ratio       0.0274   0.155  0.2098 -0.0325  0.1135   \n",
       "     CAPEX Coverage Ratio           0.6694 -0.1497  0.2154 -0.1158   0.241   \n",
       "     Dividend CAPEX Coverage Ratio  0.3378  0.0795  0.1742 -0.1102  0.1262   \n",
       "AMZN Debt-to-Assets Ratio          -0.0638  0.0537  0.0939 -0.1516 -0.1845   \n",
       "     Debt-to-Equity Ratio          -0.1128 -0.0682  0.1396 -0.2998 -0.3187   \n",
       "     Debt Service Coverage Ratio    0.0942 -0.0348 -0.5495  1.8363  0.7105   \n",
       "     Equity Multiplier              -0.043  -0.089 -0.0297 -0.0836   -0.17   \n",
       "     Free Cash Flow Yield          -0.3291 -1.5472  1.2644 -2.0457 -0.3058   \n",
       "     Net-Debt to EBITDA Ratio       0.1762  0.5435  0.1749 -0.5429 -0.4098   \n",
       "     Cash Flow Coverage Ratio       0.2847 -0.4916 -0.1616  0.8771  0.4132   \n",
       "     CAPEX Coverage Ratio          -0.2795 -0.5389 -0.0319   1.193 -0.1334   \n",
       "     Dividend CAPEX Coverage Ratio -0.2795 -0.5389 -0.0319   1.193 -0.1334   \n",
       "META Debt-to-Assets Ratio          -0.1357  0.2496  0.7129  0.1327  0.0956   \n",
       "     Debt-to-Equity Ratio          -0.1879  0.3386  0.9037  0.1494  0.1049   \n",
       "     Debt Service Coverage Ratio    0.3686  0.0144 -0.5158  0.3658  0.4117   \n",
       "     Equity Multiplier              0.0243  0.0068  0.0923  0.0611  0.0111   \n",
       "     Free Cash Flow Yield           -0.163   0.363  0.4262 -0.1834 -0.2432   \n",
       "     Net-Debt to EBITDA Ratio      -0.4054  -0.715 -7.3427 -1.2524 -1.7622   \n",
       "     Cash Flow Coverage Ratio        0.034  0.1433 -0.5435  0.0062 -0.0253   \n",
       "     CAPEX Coverage Ratio           0.0661  0.2119 -0.4831  0.6241 -0.0601   \n",
       "     Dividend CAPEX Coverage Ratio  0.0661  0.2119 -0.4831  0.6241 -0.1727   \n",
       "WMT  Debt-to-Assets Ratio           0.1576 -0.1822 -0.0655   0.035  0.0029   \n",
       "     Debt-to-Equity Ratio           0.2189 -0.1864 -0.1367  0.1246 -0.0349   \n",
       "     Debt Service Coverage Ratio    -0.067 -0.0794  0.2198 -0.2536   0.319   \n",
       "     Equity Multiplier              0.0706  0.0227 -0.0415   0.001  0.0231   \n",
       "     Free Cash Flow Yield           -0.292  0.7797 -0.5556 -0.0036 -0.2581   \n",
       "     Net-Debt to EBITDA Ratio       0.2944 -0.3233 -0.1388  0.3786 -0.1742   \n",
       "     Cash Flow Coverage Ratio      -0.2708  0.6358 -0.2605  0.1605  0.1902   \n",
       "     CAPEX Coverage Ratio          -0.1207  0.4897  -0.475 -0.0727  0.0134   \n",
       "     Dividend CAPEX Coverage Ratio -0.1067  0.4609 -0.4299 -0.0001   0.064   \n",
       "\n",
       "date                                  2025  \n",
       "AAPL Debt-to-Assets Ratio              0.0  \n",
       "     Debt-to-Equity Ratio              0.0  \n",
       "     Debt Service Coverage Ratio       0.0  \n",
       "     Equity Multiplier                 0.0  \n",
       "     Free Cash Flow Yield              0.0  \n",
       "     Net-Debt to EBITDA Ratio          0.0  \n",
       "     Cash Flow Coverage Ratio          0.0  \n",
       "     CAPEX Coverage Ratio              0.0  \n",
       "     Dividend CAPEX Coverage Ratio     0.0  \n",
       "AMZN Debt-to-Assets Ratio              0.0  \n",
       "     Debt-to-Equity Ratio              0.0  \n",
       "     Debt Service Coverage Ratio       0.0  \n",
       "     Equity Multiplier                 0.0  \n",
       "     Free Cash Flow Yield              0.0  \n",
       "     Net-Debt to EBITDA Ratio          0.0  \n",
       "     Cash Flow Coverage Ratio          0.0  \n",
       "     CAPEX Coverage Ratio              0.0  \n",
       "     Dividend CAPEX Coverage Ratio     0.0  \n",
       "META Debt-to-Assets Ratio              0.0  \n",
       "     Debt-to-Equity Ratio              0.0  \n",
       "     Debt Service Coverage Ratio       0.0  \n",
       "     Equity Multiplier                 0.0  \n",
       "     Free Cash Flow Yield              0.0  \n",
       "     Net-Debt to EBITDA Ratio          0.0  \n",
       "     Cash Flow Coverage Ratio          0.0  \n",
       "     CAPEX Coverage Ratio              0.0  \n",
       "     Dividend CAPEX Coverage Ratio     0.0  \n",
       "WMT  Debt-to-Assets Ratio          -0.0514  \n",
       "     Debt-to-Equity Ratio          -0.0911  \n",
       "     Debt Service Coverage Ratio    0.0397  \n",
       "     Equity Multiplier             -0.0398  \n",
       "     Free Cash Flow Yield           -0.256  \n",
       "     Net-Debt to EBITDA Ratio      -0.0884  \n",
       "     Cash Flow Coverage Ratio       0.0405  \n",
       "     CAPEX Coverage Ratio          -0.1162  \n",
       "     Dividend CAPEX Coverage Ratio -0.1047  \n",
       "\n",
       "[36 rows x 21 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "companies.ratios.collect_solvency_ratios(diluted=False, growth=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7ec2674",
   "metadata": {},
   "source": [
    "For all ratios, it is also possible to show the growth instead. E.g. if you are interested in the growth of the Price-to-Book ratio you can use the following:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "48b75204",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Date</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>...</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>2023</th>\n",
       "      <th>2024</th>\n",
       "      <th>2025</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.1016</td>\n",
       "      <td>0.6245</td>\n",
       "      <td>-0.7148</td>\n",
       "      <td>0.7491</td>\n",
       "      <td>0.0327</td>\n",
       "      <td>-0.2069</td>\n",
       "      <td>-0.14</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>0.4321</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0277</td>\n",
       "      <td>0.3346</td>\n",
       "      <td>0.1103</td>\n",
       "      <td>1.0492</td>\n",
       "      <td>1.3596</td>\n",
       "      <td>0.3335</td>\n",
       "      <td>-0.1181</td>\n",
       "      <td>0.1702</td>\n",
       "      <td>0.3831</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.5251</td>\n",
       "      <td>-0.1544</td>\n",
       "      <td>-0.7476</td>\n",
       "      <td>0.3673</td>\n",
       "      <td>0.0567</td>\n",
       "      <td>-0.1402</td>\n",
       "      <td>0.3489</td>\n",
       "      <td>0.3719</td>\n",
       "      <td>-0.2983</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2187</td>\n",
       "      <td>0.1057</td>\n",
       "      <td>-0.1712</td>\n",
       "      <td>-0.1298</td>\n",
       "      <td>0.1851</td>\n",
       "      <td>-0.3015</td>\n",
       "      <td>-0.5282</td>\n",
       "      <td>0.3475</td>\n",
       "      <td>0.0416</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>META</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.5251</td>\n",
       "      <td>-0.1544</td>\n",
       "      <td>-0.7476</td>\n",
       "      <td>0.3673</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>inf</td>\n",
       "      <td>0.227</td>\n",
       "      <td>-0.3524</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1581</td>\n",
       "      <td>0.2341</td>\n",
       "      <td>-0.3512</td>\n",
       "      <td>0.2834</td>\n",
       "      <td>0.0527</td>\n",
       "      <td>0.2523</td>\n",
       "      <td>-0.6641</td>\n",
       "      <td>1.3489</td>\n",
       "      <td>0.3793</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WMT</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.1002</td>\n",
       "      <td>-0.1155</td>\n",
       "      <td>0.0986</td>\n",
       "      <td>-0.0845</td>\n",
       "      <td>-0.0827</td>\n",
       "      <td>0.0782</td>\n",
       "      <td>0.0386</td>\n",
       "      <td>0.0511</td>\n",
       "      <td>0.0586</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1305</td>\n",
       "      <td>0.431</td>\n",
       "      <td>-0.0886</td>\n",
       "      <td>0.3407</td>\n",
       "      <td>0.147</td>\n",
       "      <td>-0.0806</td>\n",
       "      <td>-0.0616</td>\n",
       "      <td>0.1765</td>\n",
       "      <td>0.5545</td>\n",
       "      <td>0.0368</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Date  2005    2006    2007    2008    2009    2010    2011   2012   2013  \\\n",
       "AAPL   NaN -0.1016  0.6245 -0.7148  0.7491  0.0327 -0.2069  -0.14 -0.006   \n",
       "AMZN   NaN -0.5251 -0.1544 -0.7476  0.3673  0.0567 -0.1402 0.3489 0.3719   \n",
       "META   NaN -0.5251 -0.1544 -0.7476  0.3673    -1.0     NaN    inf  0.227   \n",
       "WMT    NaN -0.1002 -0.1155  0.0986 -0.0845 -0.0827  0.0782 0.0386 0.0511   \n",
       "\n",
       "Date    2014  ...    2016   2017    2018    2019   2020    2021    2022  \\\n",
       "AAPL  0.4321  ... -0.0277 0.3346  0.1103  1.0492 1.3596  0.3335 -0.1181   \n",
       "AMZN -0.2983  ... -0.2187 0.1057 -0.1712 -0.1298 0.1851 -0.3015 -0.5282   \n",
       "META -0.3524  ... -0.1581 0.2341 -0.3512  0.2834 0.0527  0.2523 -0.6641   \n",
       "WMT   0.0586  ...  0.1305  0.431 -0.0886  0.3407  0.147 -0.0806 -0.0616   \n",
       "\n",
       "Date   2023   2024   2025  \n",
       "AAPL 0.1702 0.3831    0.0  \n",
       "AMZN 0.3475 0.0416    0.0  \n",
       "META 1.3489 0.3793    0.0  \n",
       "WMT  0.1765 0.5545 0.0368  \n",
       "\n",
       "[4 rows x 21 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "companies.ratios.get_price_to_book_ratio(growth=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfedee0b",
   "metadata": {},
   "source": [
    "By default, the lag is set to 1 (one period) but it is possible to change this and add multiple lags as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8dae792f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>...</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>2023</th>\n",
       "      <th>2024</th>\n",
       "      <th>2025</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">AAPL</th>\n",
       "      <th>Lag 1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.2376</td>\n",
       "      <td>0.0506</td>\n",
       "      <td>0.1163</td>\n",
       "      <td>0.0384</td>\n",
       "      <td>-0.2666</td>\n",
       "      <td>-0.2003</td>\n",
       "      <td>-0.07</td>\n",
       "      <td>0.1222</td>\n",
       "      <td>-0.3566</td>\n",
       "      <td>...</td>\n",
       "      <td>0.22</td>\n",
       "      <td>-0.0566</td>\n",
       "      <td>-0.1122</td>\n",
       "      <td>0.3594</td>\n",
       "      <td>-0.1146</td>\n",
       "      <td>-0.212</td>\n",
       "      <td>-0.1817</td>\n",
       "      <td>0.1236</td>\n",
       "      <td>-0.1222</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag 2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.199</td>\n",
       "      <td>0.1728</td>\n",
       "      <td>0.1591</td>\n",
       "      <td>-0.2385</td>\n",
       "      <td>-0.4135</td>\n",
       "      <td>-0.2563</td>\n",
       "      <td>0.0436</td>\n",
       "      <td>-0.2779</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2523</td>\n",
       "      <td>0.1509</td>\n",
       "      <td>-0.1625</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.2036</td>\n",
       "      <td>-0.3023</td>\n",
       "      <td>-0.3551</td>\n",
       "      <td>-0.0805</td>\n",
       "      <td>-0.0137</td>\n",
       "      <td>-0.1222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag 3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.1059</td>\n",
       "      <td>0.2179</td>\n",
       "      <td>-0.1499</td>\n",
       "      <td>-0.391</td>\n",
       "      <td>-0.4546</td>\n",
       "      <td>-0.1654</td>\n",
       "      <td>-0.3285</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1942</td>\n",
       "      <td>0.1814</td>\n",
       "      <td>0.0218</td>\n",
       "      <td>0.1386</td>\n",
       "      <td>0.0686</td>\n",
       "      <td>-0.0515</td>\n",
       "      <td>-0.429</td>\n",
       "      <td>-0.2754</td>\n",
       "      <td>-0.1929</td>\n",
       "      <td>-0.0137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">AMZN</th>\n",
       "      <th>Lag 1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.1363</td>\n",
       "      <td>0.0437</td>\n",
       "      <td>-0.067</td>\n",
       "      <td>0.0255</td>\n",
       "      <td>-0.0038</td>\n",
       "      <td>-0.1141</td>\n",
       "      <td>-0.0455</td>\n",
       "      <td>-0.0438</td>\n",
       "      <td>0.0408</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0084</td>\n",
       "      <td>-0.0047</td>\n",
       "      <td>0.0559</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>-0.0427</td>\n",
       "      <td>0.0814</td>\n",
       "      <td>-0.1683</td>\n",
       "      <td>0.1063</td>\n",
       "      <td>0.0179</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag 2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0985</td>\n",
       "      <td>-0.0262</td>\n",
       "      <td>-0.0432</td>\n",
       "      <td>0.0217</td>\n",
       "      <td>-0.1174</td>\n",
       "      <td>-0.1544</td>\n",
       "      <td>-0.0873</td>\n",
       "      <td>-0.0049</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0632</td>\n",
       "      <td>-0.013</td>\n",
       "      <td>0.051</td>\n",
       "      <td>0.0549</td>\n",
       "      <td>-0.0436</td>\n",
       "      <td>0.0353</td>\n",
       "      <td>-0.1005</td>\n",
       "      <td>-0.0798</td>\n",
       "      <td>0.1261</td>\n",
       "      <td>0.0179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag 3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.1589</td>\n",
       "      <td>-0.0013</td>\n",
       "      <td>-0.0468</td>\n",
       "      <td>-0.0949</td>\n",
       "      <td>-0.1576</td>\n",
       "      <td>-0.1915</td>\n",
       "      <td>-0.0501</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.025</td>\n",
       "      <td>-0.0675</td>\n",
       "      <td>0.0422</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.0099</td>\n",
       "      <td>0.0343</td>\n",
       "      <td>-0.1389</td>\n",
       "      <td>-0.0049</td>\n",
       "      <td>-0.0634</td>\n",
       "      <td>0.1261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">META</th>\n",
       "      <th>Lag 1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.113</td>\n",
       "      <td>1.0913</td>\n",
       "      <td>0.1094</td>\n",
       "      <td>-0.2086</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0638</td>\n",
       "      <td>0.0794</td>\n",
       "      <td>-0.443</td>\n",
       "      <td>-0.3885</td>\n",
       "      <td>0.1481</td>\n",
       "      <td>-0.3755</td>\n",
       "      <td>-0.3015</td>\n",
       "      <td>0.2122</td>\n",
       "      <td>0.1149</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag 2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.855</td>\n",
       "      <td>1.3201</td>\n",
       "      <td>-0.122</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2725</td>\n",
       "      <td>0.1483</td>\n",
       "      <td>-0.3988</td>\n",
       "      <td>-0.6594</td>\n",
       "      <td>-0.2979</td>\n",
       "      <td>-0.283</td>\n",
       "      <td>-0.5638</td>\n",
       "      <td>-0.1532</td>\n",
       "      <td>0.3515</td>\n",
       "      <td>0.1149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag 3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0579</td>\n",
       "      <td>0.8361</td>\n",
       "      <td>...</td>\n",
       "      <td>0.007</td>\n",
       "      <td>0.3736</td>\n",
       "      <td>-0.3604</td>\n",
       "      <td>-0.6323</td>\n",
       "      <td>-0.6089</td>\n",
       "      <td>-0.5615</td>\n",
       "      <td>-0.4992</td>\n",
       "      <td>-0.4712</td>\n",
       "      <td>-0.0559</td>\n",
       "      <td>0.3515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">WMT</th>\n",
       "      <th>Lag 1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0024</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>-0.0885</td>\n",
       "      <td>0.0762</td>\n",
       "      <td>-0.0214</td>\n",
       "      <td>0.0263</td>\n",
       "      <td>-0.0058</td>\n",
       "      <td>-0.0542</td>\n",
       "      <td>0.0572</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0387</td>\n",
       "      <td>-0.0754</td>\n",
       "      <td>-0.1185</td>\n",
       "      <td>0.0514</td>\n",
       "      <td>-0.0055</td>\n",
       "      <td>0.2236</td>\n",
       "      <td>-0.0456</td>\n",
       "      <td>-0.1156</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>-0.011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag 2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0013</td>\n",
       "      <td>-0.0851</td>\n",
       "      <td>-0.0191</td>\n",
       "      <td>0.0531</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>-0.0596</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0565</td>\n",
       "      <td>-0.1111</td>\n",
       "      <td>-0.1849</td>\n",
       "      <td>-0.0731</td>\n",
       "      <td>0.0456</td>\n",
       "      <td>0.2169</td>\n",
       "      <td>0.1677</td>\n",
       "      <td>-0.1559</td>\n",
       "      <td>-0.1034</td>\n",
       "      <td>0.0026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag 3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0874</td>\n",
       "      <td>-0.0155</td>\n",
       "      <td>-0.0401</td>\n",
       "      <td>0.0808</td>\n",
       "      <td>-0.0015</td>\n",
       "      <td>-0.0349</td>\n",
       "      <td>-0.0059</td>\n",
       "      <td>...</td>\n",
       "      <td>0.117</td>\n",
       "      <td>-0.0231</td>\n",
       "      <td>-0.2164</td>\n",
       "      <td>-0.143</td>\n",
       "      <td>-0.0782</td>\n",
       "      <td>0.2794</td>\n",
       "      <td>0.1613</td>\n",
       "      <td>0.0328</td>\n",
       "      <td>-0.1443</td>\n",
       "      <td>-0.1133</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "date        2005    2006    2007    2008    2009    2010    2011    2012  \\\n",
       "AAPL Lag 1   NaN -0.2376  0.0506  0.1163  0.0384 -0.2666 -0.2003   -0.07   \n",
       "     Lag 2   NaN     NaN  -0.199  0.1728  0.1591 -0.2385 -0.4135 -0.2563   \n",
       "     Lag 3   NaN     NaN     NaN -0.1059  0.2179 -0.1499  -0.391 -0.4546   \n",
       "AMZN Lag 1   NaN -0.1363  0.0437  -0.067  0.0255 -0.0038 -0.1141 -0.0455   \n",
       "     Lag 2   NaN     NaN -0.0985 -0.0262 -0.0432  0.0217 -0.1174 -0.1544   \n",
       "     Lag 3   NaN     NaN     NaN -0.1589 -0.0013 -0.0468 -0.0949 -0.1576   \n",
       "META Lag 1   NaN     NaN     NaN     NaN     NaN     NaN  -0.113  1.0913   \n",
       "     Lag 2   NaN     NaN     NaN     NaN     NaN     NaN     NaN   0.855   \n",
       "     Lag 3   NaN     NaN     NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "WMT  Lag 1   NaN -0.0024  0.0037 -0.0885  0.0762 -0.0214  0.0263 -0.0058   \n",
       "     Lag 2   NaN     NaN  0.0013 -0.0851 -0.0191  0.0531  0.0043  0.0204   \n",
       "     Lag 3   NaN     NaN     NaN -0.0874 -0.0155 -0.0401  0.0808 -0.0015   \n",
       "\n",
       "date          2013    2014  ...    2016    2017    2018    2019    2020  \\\n",
       "AAPL Lag 1  0.1222 -0.3566  ...    0.22 -0.0566 -0.1122  0.3594 -0.1146   \n",
       "     Lag 2  0.0436 -0.2779  ...  0.2523  0.1509 -0.1625  0.2069  0.2036   \n",
       "     Lag 3 -0.1654 -0.3285  ... -0.1942  0.1814  0.0218  0.1386  0.0686   \n",
       "AMZN Lag 1 -0.0438  0.0408  ... -0.0084 -0.0047  0.0559  -0.001 -0.0427   \n",
       "     Lag 2 -0.0873 -0.0049  ... -0.0632  -0.013   0.051  0.0549 -0.0436   \n",
       "     Lag 3 -0.1915 -0.0501  ...  -0.025 -0.0675  0.0422    0.05  0.0099   \n",
       "META Lag 1  0.1094 -0.2086  ...  0.0638  0.0794  -0.443 -0.3885  0.1481   \n",
       "     Lag 2  1.3201  -0.122  ...  0.2725  0.1483 -0.3988 -0.6594 -0.2979   \n",
       "     Lag 3  1.0579  0.8361  ...   0.007  0.3736 -0.3604 -0.6323 -0.6089   \n",
       "WMT  Lag 1 -0.0542  0.0572  ... -0.0387 -0.0754 -0.1185  0.0514 -0.0055   \n",
       "     Lag 2 -0.0596 -0.0001  ...  0.0565 -0.1111 -0.1849 -0.0731  0.0456   \n",
       "     Lag 3 -0.0349 -0.0059  ...   0.117 -0.0231 -0.2164  -0.143 -0.0782   \n",
       "\n",
       "date          2021    2022    2023    2024    2025  \n",
       "AAPL Lag 1  -0.212 -0.1817  0.1236 -0.1222     0.0  \n",
       "     Lag 2 -0.3023 -0.3551 -0.0805 -0.0137 -0.1222  \n",
       "     Lag 3 -0.0515  -0.429 -0.2754 -0.1929 -0.0137  \n",
       "AMZN Lag 1  0.0814 -0.1683  0.1063  0.0179     0.0  \n",
       "     Lag 2  0.0353 -0.1005 -0.0798  0.1261  0.0179  \n",
       "     Lag 3  0.0343 -0.1389 -0.0049 -0.0634  0.1261  \n",
       "META Lag 1 -0.3755 -0.3015  0.2122  0.1149     0.0  \n",
       "     Lag 2  -0.283 -0.5638 -0.1532  0.3515  0.1149  \n",
       "     Lag 3 -0.5615 -0.4992 -0.4712 -0.0559  0.3515  \n",
       "WMT  Lag 1  0.2236 -0.0456 -0.1156  0.0138  -0.011  \n",
       "     Lag 2  0.2169  0.1677 -0.1559 -0.1034  0.0026  \n",
       "     Lag 3  0.2794  0.1613  0.0328 -0.1443 -0.1133  \n",
       "\n",
       "[12 rows x 21 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "companies.ratios.get_current_ratio(growth=True, lag=[1, 2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4408750c",
   "metadata": {},
   "source": [
    "It is also possible to get trailing results. E.g. the TTM Earnings per Share ratio can be acquired by setting trailing to 4 (quarters). Note that this does not lead to meaningful results when using yearly data and therefore this image now shows the 4 year trailing result. Set `quarterly=True` in the Toolkit initialization to use quarterly data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f28ffcb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': '4 Year Trailing Earnings per Share Growth for Apple, Amazon, META and Walmart'}, xlabel='Date', ylabel='Earnings per Share Growth'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "companies.ratios.get_earnings_per_share(trailing=4).T.dropna().plot(\n",
    "    figsize=(15, 3),\n",
    "    title=\"4 Year Trailing Earnings per Share for Apple, Amazon, META and Walmart\",\n",
    "    grid=True,\n",
    "    linestyle=\"-\",\n",
    "    linewidth=2,\n",
    "    xlabel=\"Date\",\n",
    "    ylabel=\"Earnings per Share\",\n",
    ")\n",
    "\n",
    "companies.ratios.get_earnings_per_share(trailing=4, growth=True).T.dropna().plot(\n",
    "    figsize=(15, 3),\n",
    "    title=\"4 Year Trailing Earnings per Share Growth for Apple, Amazon, META and Walmart\",\n",
    "    grid=True,\n",
    "    linestyle=\"-\",\n",
    "    linewidth=2,\n",
    "    xlabel=\"Date\",\n",
    "    ylabel=\"Earnings per Share Growth\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "658d7f7b",
   "metadata": {},
   "source": [
    "It is possible to define custom ratios if the current ratio calculations are not sufficient. Define how each custom ratio needs to be calculated. This can be any of the following structures:\n",
    "\n",
    "- **Simple operations such as:** `'Quick Assets': 'Cash and Short Term Investments + Accounts Receivable'`\n",
    "- **Working with multiple operations:** `'Cash Op Expenses':'Cost of Goods Sold + Selling, General and Administrative Expenses - Depreciation and Amortization'`,\n",
    "- **Using curly brackets:** `'WC / Net Income as %': '(Working Capital / Net Income) * 100'`,\n",
    "- **Defining a criteria:** `'Large Revenues': 'Revenue > 1000000000'`,\n",
    "- **Using actual numbers:**  `'Daily Cash Op Expenses': 'Cash Op Expenses / 365'`,\n",
    "- **Combining earlier defined formulas:** `'Defensive Interval':'Quick Assets / Daily Cash Op Expenses'`\n",
    "\n",
    "Not that it is important you follow the NAME - FORMULA format and that you adhere to the financial statement naming. See some of the available fields you can use below, shrunken down for readability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ee2da2f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2025-09-09 16:40:22 - financetoolkit - INFO - The following names are available to be used in the Custom Ratios calculations.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['Asset Turnover Ratio',\n",
       " 'Book Value per Share',\n",
       " 'CAPEX Coverage Ratio',\n",
       " 'CAPEX per Share',\n",
       " 'Capital Expenditure']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "companies.ratios.collect_custom_ratios(options=True)[10:15]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19853ba6",
   "metadata": {},
   "source": [
    "Then create your custom ratios and add them to custom ratios function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1fe66edb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>...</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>2023</th>\n",
       "      <th>2024</th>\n",
       "      <th>2025</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">AAPL</th>\n",
       "      <th>WC / Net Income as %</th>\n",
       "      <td>513.0271</td>\n",
       "      <td>405.5304</td>\n",
       "      <td>362.6896</td>\n",
       "      <td>385.7054</td>\n",
       "      <td>243.4608</td>\n",
       "      <td>149.5468</td>\n",
       "      <td>65.6508</td>\n",
       "      <td>45.7935</td>\n",
       "      <td>79.9957</td>\n",
       "      <td>12.8651</td>\n",
       "      <td>...</td>\n",
       "      <td>60.9867</td>\n",
       "      <td>57.5603</td>\n",
       "      <td>25.8857</td>\n",
       "      <td>103.339</td>\n",
       "      <td>66.7485</td>\n",
       "      <td>9.8807</td>\n",
       "      <td>-18.6137</td>\n",
       "      <td>-1.796</td>\n",
       "      <td>-24.9691</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Large Revenues</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Quick Assets</th>\n",
       "      <td>9156000000.0</td>\n",
       "      <td>11362000000.0</td>\n",
       "      <td>17023000000.0</td>\n",
       "      <td>24533000000.0</td>\n",
       "      <td>26825000000.0</td>\n",
       "      <td>31130000000.0</td>\n",
       "      <td>31321000000.0</td>\n",
       "      <td>40059000000.0</td>\n",
       "      <td>53648000000.0</td>\n",
       "      <td>42537000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>82909000000.0</td>\n",
       "      <td>92055000000.0</td>\n",
       "      <td>89487000000.0</td>\n",
       "      <td>123483000000.0</td>\n",
       "      <td>107063000000.0</td>\n",
       "      <td>88917000000.0</td>\n",
       "      <td>76488000000.0</td>\n",
       "      <td>91063000000.0</td>\n",
       "      <td>98581000000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash Op Expenses</th>\n",
       "      <td>11574000000.0</td>\n",
       "      <td>15925000000.0</td>\n",
       "      <td>18498000000.0</td>\n",
       "      <td>24686000000.0</td>\n",
       "      <td>29098000000.0</td>\n",
       "      <td>44031000000.0</td>\n",
       "      <td>70216000000.0</td>\n",
       "      <td>94609000000.0</td>\n",
       "      <td>110679000000.0</td>\n",
       "      <td>116305000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>135065000000.0</td>\n",
       "      <td>146152000000.0</td>\n",
       "      <td>169558000000.0</td>\n",
       "      <td>167480000000.0</td>\n",
       "      <td>178419000000.0</td>\n",
       "      <td>223670000000.0</td>\n",
       "      <td>237536000000.0</td>\n",
       "      <td>227550000000.0</td>\n",
       "      <td>225004000000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily Cash Op Expenses</th>\n",
       "      <td>31709589.0411</td>\n",
       "      <td>43630136.9863</td>\n",
       "      <td>50679452.0548</td>\n",
       "      <td>67632876.7123</td>\n",
       "      <td>79720547.9452</td>\n",
       "      <td>120632876.7123</td>\n",
       "      <td>192372602.7397</td>\n",
       "      <td>259202739.726</td>\n",
       "      <td>303230136.9863</td>\n",
       "      <td>318643835.6164</td>\n",
       "      <td>...</td>\n",
       "      <td>370041095.8904</td>\n",
       "      <td>400416438.3562</td>\n",
       "      <td>464542465.7534</td>\n",
       "      <td>458849315.0685</td>\n",
       "      <td>488819178.0822</td>\n",
       "      <td>612794520.5479</td>\n",
       "      <td>650783561.6438</td>\n",
       "      <td>623424657.5342</td>\n",
       "      <td>616449315.0685</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Defensive Interval</th>\n",
       "      <td>288.7455</td>\n",
       "      <td>260.4163</td>\n",
       "      <td>335.8955</td>\n",
       "      <td>362.7378</td>\n",
       "      <td>336.4879</td>\n",
       "      <td>258.0557</td>\n",
       "      <td>162.8142</td>\n",
       "      <td>154.547</td>\n",
       "      <td>176.9217</td>\n",
       "      <td>133.4939</td>\n",
       "      <td>...</td>\n",
       "      <td>224.0535</td>\n",
       "      <td>229.8982</td>\n",
       "      <td>192.6347</td>\n",
       "      <td>269.1145</td>\n",
       "      <td>219.0237</td>\n",
       "      <td>145.1008</td>\n",
       "      <td>117.5322</td>\n",
       "      <td>146.069</td>\n",
       "      <td>159.9174</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">AMZN</th>\n",
       "      <th>WC / Net Income as %</th>\n",
       "      <td>286.9081</td>\n",
       "      <td>442.6316</td>\n",
       "      <td>304.6218</td>\n",
       "      <td>218.7597</td>\n",
       "      <td>269.7339</td>\n",
       "      <td>292.9688</td>\n",
       "      <td>411.0935</td>\n",
       "      <td>-5882.0513</td>\n",
       "      <td>600.365</td>\n",
       "      <td>-1343.5685</td>\n",
       "      <td>...</td>\n",
       "      <td>82.8764</td>\n",
       "      <td>76.2941</td>\n",
       "      <td>66.6137</td>\n",
       "      <td>73.5416</td>\n",
       "      <td>29.7595</td>\n",
       "      <td>57.8887</td>\n",
       "      <td>316.0176</td>\n",
       "      <td>24.4339</td>\n",
       "      <td>19.3019</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Large Revenues</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Quick Assets</th>\n",
       "      <td>2274000000.0</td>\n",
       "      <td>2418000000.0</td>\n",
       "      <td>4522000000.0</td>\n",
       "      <td>5381000000.0</td>\n",
       "      <td>7354000000.0</td>\n",
       "      <td>10349000000.0</td>\n",
       "      <td>12147000000.0</td>\n",
       "      <td>15265000000.0</td>\n",
       "      <td>17214000000.0</td>\n",
       "      <td>23028000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>34320000000.0</td>\n",
       "      <td>44150000000.0</td>\n",
       "      <td>57927000000.0</td>\n",
       "      <td>75837000000.0</td>\n",
       "      <td>108938000000.0</td>\n",
       "      <td>128940000000.0</td>\n",
       "      <td>112386000000.0</td>\n",
       "      <td>139033000000.0</td>\n",
       "      <td>156653000000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash Op Expenses</th>\n",
       "      <td>6694000000.0</td>\n",
       "      <td>8508000000.0</td>\n",
       "      <td>11815000000.0</td>\n",
       "      <td>15370000000.0</td>\n",
       "      <td>19608000000.0</td>\n",
       "      <td>27492000000.0</td>\n",
       "      <td>38493000000.0</td>\n",
       "      <td>47116000000.0</td>\n",
       "      <td>55190000000.0</td>\n",
       "      <td>63890000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>89814000000.0</td>\n",
       "      <td>114199000000.0</td>\n",
       "      <td>141965000000.0</td>\n",
       "      <td>167828000000.0</td>\n",
       "      <td>236803000000.0</td>\n",
       "      <td>279285000000.0</td>\n",
       "      <td>301039000000.0</td>\n",
       "      <td>312262000000.0</td>\n",
       "      <td>328759000000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily Cash Op Expenses</th>\n",
       "      <td>18339726.0274</td>\n",
       "      <td>23309589.0411</td>\n",
       "      <td>32369863.0137</td>\n",
       "      <td>42109589.0411</td>\n",
       "      <td>53720547.9452</td>\n",
       "      <td>75320547.9452</td>\n",
       "      <td>105460273.9726</td>\n",
       "      <td>129084931.5068</td>\n",
       "      <td>151205479.4521</td>\n",
       "      <td>175041095.8904</td>\n",
       "      <td>...</td>\n",
       "      <td>246065753.4247</td>\n",
       "      <td>312873972.6027</td>\n",
       "      <td>388945205.4795</td>\n",
       "      <td>459802739.726</td>\n",
       "      <td>648775342.4658</td>\n",
       "      <td>765164383.5616</td>\n",
       "      <td>824764383.5616</td>\n",
       "      <td>855512328.7671</td>\n",
       "      <td>900709589.0411</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Defensive Interval</th>\n",
       "      <td>123.9931</td>\n",
       "      <td>103.7341</td>\n",
       "      <td>139.6978</td>\n",
       "      <td>127.7856</td>\n",
       "      <td>136.8936</td>\n",
       "      <td>137.3994</td>\n",
       "      <td>115.1808</td>\n",
       "      <td>118.2555</td>\n",
       "      <td>113.8451</td>\n",
       "      <td>131.5577</td>\n",
       "      <td>...</td>\n",
       "      <td>139.4749</td>\n",
       "      <td>141.1111</td>\n",
       "      <td>148.9336</td>\n",
       "      <td>164.9338</td>\n",
       "      <td>167.9133</td>\n",
       "      <td>168.5128</td>\n",
       "      <td>136.2644</td>\n",
       "      <td>162.5143</td>\n",
       "      <td>173.9218</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">META</th>\n",
       "      <th>WC / Net Income as %</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>461.9403</td>\n",
       "      <td>370.5</td>\n",
       "      <td>19273.5849</td>\n",
       "      <td>798.0</td>\n",
       "      <td>407.0068</td>\n",
       "      <td>...</td>\n",
       "      <td>308.5642</td>\n",
       "      <td>281.1786</td>\n",
       "      <td>196.5673</td>\n",
       "      <td>276.8299</td>\n",
       "      <td>208.2241</td>\n",
       "      <td>115.649</td>\n",
       "      <td>140.1853</td>\n",
       "      <td>136.5927</td>\n",
       "      <td>106.5571</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Large Revenues</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Quick Assets</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2158000000.0</td>\n",
       "      <td>4455000000.0</td>\n",
       "      <td>10345000000.0</td>\n",
       "      <td>12558000000.0</td>\n",
       "      <td>12877000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33442000000.0</td>\n",
       "      <td>47543000000.0</td>\n",
       "      <td>48701000000.0</td>\n",
       "      <td>64373000000.0</td>\n",
       "      <td>73289000000.0</td>\n",
       "      <td>62037000000.0</td>\n",
       "      <td>54204000000.0</td>\n",
       "      <td>81572000000.0</td>\n",
       "      <td>94809000000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash Op Expenses</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>196000000.0</td>\n",
       "      <td>280000000.0</td>\n",
       "      <td>350000000.0</td>\n",
       "      <td>659000000.0</td>\n",
       "      <td>1244000000.0</td>\n",
       "      <td>2503000000.0</td>\n",
       "      <td>2642000000.0</td>\n",
       "      <td>3563000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6950000000.0</td>\n",
       "      <td>9671000000.0</td>\n",
       "      <td>16337000000.0</td>\n",
       "      <td>27370000000.0</td>\n",
       "      <td>27985000000.0</td>\n",
       "      <td>38554000000.0</td>\n",
       "      <td>43641000000.0</td>\n",
       "      <td>38490000000.0</td>\n",
       "      <td>35750000000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily Cash Op Expenses</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>536986.3014</td>\n",
       "      <td>767123.2877</td>\n",
       "      <td>958904.1096</td>\n",
       "      <td>1805479.4521</td>\n",
       "      <td>3408219.1781</td>\n",
       "      <td>6857534.2466</td>\n",
       "      <td>7238356.1644</td>\n",
       "      <td>9761643.8356</td>\n",
       "      <td>...</td>\n",
       "      <td>19041095.8904</td>\n",
       "      <td>26495890.411</td>\n",
       "      <td>44758904.1096</td>\n",
       "      <td>74986301.3699</td>\n",
       "      <td>76671232.8767</td>\n",
       "      <td>105627397.2603</td>\n",
       "      <td>119564383.5616</td>\n",
       "      <td>105452054.7945</td>\n",
       "      <td>97945205.4795</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Defensive Interval</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1195.2504</td>\n",
       "      <td>1307.1342</td>\n",
       "      <td>1508.5597</td>\n",
       "      <td>1734.9243</td>\n",
       "      <td>1319.1426</td>\n",
       "      <td>...</td>\n",
       "      <td>1756.3065</td>\n",
       "      <td>1794.3537</td>\n",
       "      <td>1088.074</td>\n",
       "      <td>858.4635</td>\n",
       "      <td>955.8865</td>\n",
       "      <td>587.3192</td>\n",
       "      <td>453.3457</td>\n",
       "      <td>773.5459</td>\n",
       "      <td>967.98</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">WMT</th>\n",
       "      <th>WC / Net Income as %</th>\n",
       "      <td>-42.1545</td>\n",
       "      <td>-44.5196</td>\n",
       "      <td>-45.7816</td>\n",
       "      <td>-82.1459</td>\n",
       "      <td>-48.1354</td>\n",
       "      <td>-52.2686</td>\n",
       "      <td>-40.216</td>\n",
       "      <td>-46.659</td>\n",
       "      <td>-69.8747</td>\n",
       "      <td>-50.93</td>\n",
       "      <td>...</td>\n",
       "      <td>-29.8081</td>\n",
       "      <td>-67.7197</td>\n",
       "      <td>-191.2087</td>\n",
       "      <td>-233.5832</td>\n",
       "      <td>-107.4121</td>\n",
       "      <td>-19.0822</td>\n",
       "      <td>-46.142</td>\n",
       "      <td>-141.6353</td>\n",
       "      <td>-100.1741</td>\n",
       "      <td>-88.1148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Large Revenues</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Quick Assets</th>\n",
       "      <td>7203000000.0</td>\n",
       "      <td>8768000000.0</td>\n",
       "      <td>10607000000.0</td>\n",
       "      <td>9134000000.0</td>\n",
       "      <td>11180000000.0</td>\n",
       "      <td>12051000000.0</td>\n",
       "      <td>12484000000.0</td>\n",
       "      <td>12487000000.0</td>\n",
       "      <td>14549000000.0</td>\n",
       "      <td>13958000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>14329000000.0</td>\n",
       "      <td>12702000000.0</td>\n",
       "      <td>12370000000.0</td>\n",
       "      <td>14005000000.0</td>\n",
       "      <td>15749000000.0</td>\n",
       "      <td>24257000000.0</td>\n",
       "      <td>23040000000.0</td>\n",
       "      <td>16558000000.0</td>\n",
       "      <td>18663000000.0</td>\n",
       "      <td>19012000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash Op Expenses</th>\n",
       "      <td>266713000000.0</td>\n",
       "      <td>288671000000.0</td>\n",
       "      <td>322694000000.0</td>\n",
       "      <td>350486000000.0</td>\n",
       "      <td>376070000000.0</td>\n",
       "      <td>377107000000.0</td>\n",
       "      <td>388666000000.0</td>\n",
       "      <td>412262000000.0</td>\n",
       "      <td>432860000000.0</td>\n",
       "      <td>440552000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>448571000000.0</td>\n",
       "      <td>453029000000.0</td>\n",
       "      <td>469377000000.0</td>\n",
       "      <td>481770000000.0</td>\n",
       "      <td>492409000000.0</td>\n",
       "      <td>525451000000.0</td>\n",
       "      <td>536154000000.0</td>\n",
       "      <td>579916000000.0</td>\n",
       "      <td>609260000000.0</td>\n",
       "      <td>638664000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily Cash Op Expenses</th>\n",
       "      <td>730720547.9452</td>\n",
       "      <td>790879452.0548</td>\n",
       "      <td>884093150.6849</td>\n",
       "      <td>960235616.4384</td>\n",
       "      <td>1030328767.1233</td>\n",
       "      <td>1033169863.0137</td>\n",
       "      <td>1064838356.1644</td>\n",
       "      <td>1129484931.5068</td>\n",
       "      <td>1185917808.2192</td>\n",
       "      <td>1206991780.8219</td>\n",
       "      <td>...</td>\n",
       "      <td>1228961643.8356</td>\n",
       "      <td>1241175342.4658</td>\n",
       "      <td>1285964383.5616</td>\n",
       "      <td>1319917808.2192</td>\n",
       "      <td>1349065753.4247</td>\n",
       "      <td>1439591780.8219</td>\n",
       "      <td>1468915068.4932</td>\n",
       "      <td>1588810958.9041</td>\n",
       "      <td>1669205479.4521</td>\n",
       "      <td>1749764383.5616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Defensive Interval</th>\n",
       "      <td>9.8574</td>\n",
       "      <td>11.0864</td>\n",
       "      <td>11.9976</td>\n",
       "      <td>9.5122</td>\n",
       "      <td>10.8509</td>\n",
       "      <td>11.6641</td>\n",
       "      <td>11.7238</td>\n",
       "      <td>11.0555</td>\n",
       "      <td>12.2681</td>\n",
       "      <td>11.5643</td>\n",
       "      <td>...</td>\n",
       "      <td>11.6594</td>\n",
       "      <td>10.2338</td>\n",
       "      <td>9.6192</td>\n",
       "      <td>10.6105</td>\n",
       "      <td>11.674</td>\n",
       "      <td>16.8499</td>\n",
       "      <td>15.685</td>\n",
       "      <td>10.4216</td>\n",
       "      <td>11.1808</td>\n",
       "      <td>10.8655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      2005           2006           2007  \\\n",
       "AAPL WC / Net Income as %         513.0271       405.5304       362.6896   \n",
       "     Large Revenues                    1.0            1.0            1.0   \n",
       "     Quick Assets             9156000000.0  11362000000.0  17023000000.0   \n",
       "     Cash Op Expenses        11574000000.0  15925000000.0  18498000000.0   \n",
       "     Daily Cash Op Expenses  31709589.0411  43630136.9863  50679452.0548   \n",
       "     Defensive Interval           288.7455       260.4163       335.8955   \n",
       "AMZN WC / Net Income as %         286.9081       442.6316       304.6218   \n",
       "     Large Revenues                    1.0            1.0            1.0   \n",
       "     Quick Assets             2274000000.0   2418000000.0   4522000000.0   \n",
       "     Cash Op Expenses         6694000000.0   8508000000.0  11815000000.0   \n",
       "     Daily Cash Op Expenses  18339726.0274  23309589.0411  32369863.0137   \n",
       "     Defensive Interval           123.9931       103.7341       139.6978   \n",
       "META WC / Net Income as %              NaN            NaN            NaN   \n",
       "     Large Revenues                    0.0            0.0            0.0   \n",
       "     Quick Assets                      NaN            NaN            NaN   \n",
       "     Cash Op Expenses                  NaN            NaN    196000000.0   \n",
       "     Daily Cash Op Expenses            NaN            NaN    536986.3014   \n",
       "     Defensive Interval                NaN            NaN            NaN   \n",
       "WMT  WC / Net Income as %         -42.1545       -44.5196       -45.7816   \n",
       "     Large Revenues                    1.0            1.0            1.0   \n",
       "     Quick Assets             7203000000.0   8768000000.0  10607000000.0   \n",
       "     Cash Op Expenses       266713000000.0 288671000000.0 322694000000.0   \n",
       "     Daily Cash Op Expenses 730720547.9452 790879452.0548 884093150.6849   \n",
       "     Defensive Interval             9.8574        11.0864        11.9976   \n",
       "\n",
       "                                      2008            2009            2010  \\\n",
       "AAPL WC / Net Income as %         385.7054        243.4608        149.5468   \n",
       "     Large Revenues                    1.0             1.0             1.0   \n",
       "     Quick Assets            24533000000.0   26825000000.0   31130000000.0   \n",
       "     Cash Op Expenses        24686000000.0   29098000000.0   44031000000.0   \n",
       "     Daily Cash Op Expenses  67632876.7123   79720547.9452  120632876.7123   \n",
       "     Defensive Interval           362.7378        336.4879        258.0557   \n",
       "AMZN WC / Net Income as %         218.7597        269.7339        292.9688   \n",
       "     Large Revenues                    1.0             1.0             1.0   \n",
       "     Quick Assets             5381000000.0    7354000000.0   10349000000.0   \n",
       "     Cash Op Expenses        15370000000.0   19608000000.0   27492000000.0   \n",
       "     Daily Cash Op Expenses  42109589.0411   53720547.9452   75320547.9452   \n",
       "     Defensive Interval           127.7856        136.8936        137.3994   \n",
       "META WC / Net Income as %              NaN             NaN        461.9403   \n",
       "     Large Revenues                    0.0             0.0             1.0   \n",
       "     Quick Assets                      NaN             NaN    2158000000.0   \n",
       "     Cash Op Expenses          280000000.0     350000000.0     659000000.0   \n",
       "     Daily Cash Op Expenses    767123.2877     958904.1096    1805479.4521   \n",
       "     Defensive Interval                NaN             NaN       1195.2504   \n",
       "WMT  WC / Net Income as %         -82.1459        -48.1354        -52.2686   \n",
       "     Large Revenues                    1.0             1.0             1.0   \n",
       "     Quick Assets             9134000000.0   11180000000.0   12051000000.0   \n",
       "     Cash Op Expenses       350486000000.0  376070000000.0  377107000000.0   \n",
       "     Daily Cash Op Expenses 960235616.4384 1030328767.1233 1033169863.0137   \n",
       "     Defensive Interval             9.5122         10.8509         11.6641   \n",
       "\n",
       "                                       2011            2012            2013  \\\n",
       "AAPL WC / Net Income as %           65.6508         45.7935         79.9957   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             31321000000.0   40059000000.0   53648000000.0   \n",
       "     Cash Op Expenses         70216000000.0   94609000000.0  110679000000.0   \n",
       "     Daily Cash Op Expenses  192372602.7397   259202739.726  303230136.9863   \n",
       "     Defensive Interval            162.8142         154.547        176.9217   \n",
       "AMZN WC / Net Income as %          411.0935      -5882.0513         600.365   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             12147000000.0   15265000000.0   17214000000.0   \n",
       "     Cash Op Expenses         38493000000.0   47116000000.0   55190000000.0   \n",
       "     Daily Cash Op Expenses  105460273.9726  129084931.5068  151205479.4521   \n",
       "     Defensive Interval            115.1808        118.2555        113.8451   \n",
       "META WC / Net Income as %             370.5      19273.5849           798.0   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets              4455000000.0   10345000000.0   12558000000.0   \n",
       "     Cash Op Expenses          1244000000.0    2503000000.0    2642000000.0   \n",
       "     Daily Cash Op Expenses    3408219.1781    6857534.2466    7238356.1644   \n",
       "     Defensive Interval           1307.1342       1508.5597       1734.9243   \n",
       "WMT  WC / Net Income as %           -40.216         -46.659        -69.8747   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             12484000000.0   12487000000.0   14549000000.0   \n",
       "     Cash Op Expenses        388666000000.0  412262000000.0  432860000000.0   \n",
       "     Daily Cash Op Expenses 1064838356.1644 1129484931.5068 1185917808.2192   \n",
       "     Defensive Interval             11.7238         11.0555         12.2681   \n",
       "\n",
       "                                       2014  ...            2016  \\\n",
       "AAPL WC / Net Income as %           12.8651  ...         60.9867   \n",
       "     Large Revenues                     1.0  ...             1.0   \n",
       "     Quick Assets             42537000000.0  ...   82909000000.0   \n",
       "     Cash Op Expenses        116305000000.0  ...  135065000000.0   \n",
       "     Daily Cash Op Expenses  318643835.6164  ...  370041095.8904   \n",
       "     Defensive Interval            133.4939  ...        224.0535   \n",
       "AMZN WC / Net Income as %        -1343.5685  ...         82.8764   \n",
       "     Large Revenues                     1.0  ...             1.0   \n",
       "     Quick Assets             23028000000.0  ...   34320000000.0   \n",
       "     Cash Op Expenses         63890000000.0  ...   89814000000.0   \n",
       "     Daily Cash Op Expenses  175041095.8904  ...  246065753.4247   \n",
       "     Defensive Interval            131.5577  ...        139.4749   \n",
       "META WC / Net Income as %          407.0068  ...        308.5642   \n",
       "     Large Revenues                     1.0  ...             1.0   \n",
       "     Quick Assets             12877000000.0  ...   33442000000.0   \n",
       "     Cash Op Expenses          3563000000.0  ...    6950000000.0   \n",
       "     Daily Cash Op Expenses    9761643.8356  ...   19041095.8904   \n",
       "     Defensive Interval           1319.1426  ...       1756.3065   \n",
       "WMT  WC / Net Income as %            -50.93  ...        -29.8081   \n",
       "     Large Revenues                     1.0  ...             1.0   \n",
       "     Quick Assets             13958000000.0  ...   14329000000.0   \n",
       "     Cash Op Expenses        440552000000.0  ...  448571000000.0   \n",
       "     Daily Cash Op Expenses 1206991780.8219  ... 1228961643.8356   \n",
       "     Defensive Interval             11.5643  ...         11.6594   \n",
       "\n",
       "                                       2017            2018            2019  \\\n",
       "AAPL WC / Net Income as %           57.5603         25.8857         103.339   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             92055000000.0   89487000000.0  123483000000.0   \n",
       "     Cash Op Expenses        146152000000.0  169558000000.0  167480000000.0   \n",
       "     Daily Cash Op Expenses  400416438.3562  464542465.7534  458849315.0685   \n",
       "     Defensive Interval            229.8982        192.6347        269.1145   \n",
       "AMZN WC / Net Income as %           76.2941         66.6137         73.5416   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             44150000000.0   57927000000.0   75837000000.0   \n",
       "     Cash Op Expenses        114199000000.0  141965000000.0  167828000000.0   \n",
       "     Daily Cash Op Expenses  312873972.6027  388945205.4795   459802739.726   \n",
       "     Defensive Interval            141.1111        148.9336        164.9338   \n",
       "META WC / Net Income as %          281.1786        196.5673        276.8299   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             47543000000.0   48701000000.0   64373000000.0   \n",
       "     Cash Op Expenses          9671000000.0   16337000000.0   27370000000.0   \n",
       "     Daily Cash Op Expenses    26495890.411   44758904.1096   74986301.3699   \n",
       "     Defensive Interval           1794.3537        1088.074        858.4635   \n",
       "WMT  WC / Net Income as %          -67.7197       -191.2087       -233.5832   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             12702000000.0   12370000000.0   14005000000.0   \n",
       "     Cash Op Expenses        453029000000.0  469377000000.0  481770000000.0   \n",
       "     Daily Cash Op Expenses 1241175342.4658 1285964383.5616 1319917808.2192   \n",
       "     Defensive Interval             10.2338          9.6192         10.6105   \n",
       "\n",
       "                                       2020            2021            2022  \\\n",
       "AAPL WC / Net Income as %           66.7485          9.8807        -18.6137   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets            107063000000.0   88917000000.0   76488000000.0   \n",
       "     Cash Op Expenses        178419000000.0  223670000000.0  237536000000.0   \n",
       "     Daily Cash Op Expenses  488819178.0822  612794520.5479  650783561.6438   \n",
       "     Defensive Interval            219.0237        145.1008        117.5322   \n",
       "AMZN WC / Net Income as %           29.7595         57.8887        316.0176   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets            108938000000.0  128940000000.0  112386000000.0   \n",
       "     Cash Op Expenses        236803000000.0  279285000000.0  301039000000.0   \n",
       "     Daily Cash Op Expenses  648775342.4658  765164383.5616  824764383.5616   \n",
       "     Defensive Interval            167.9133        168.5128        136.2644   \n",
       "META WC / Net Income as %          208.2241         115.649        140.1853   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             73289000000.0   62037000000.0   54204000000.0   \n",
       "     Cash Op Expenses         27985000000.0   38554000000.0   43641000000.0   \n",
       "     Daily Cash Op Expenses   76671232.8767  105627397.2603  119564383.5616   \n",
       "     Defensive Interval            955.8865        587.3192        453.3457   \n",
       "WMT  WC / Net Income as %         -107.4121        -19.0822         -46.142   \n",
       "     Large Revenues                     1.0             1.0             1.0   \n",
       "     Quick Assets             15749000000.0   24257000000.0   23040000000.0   \n",
       "     Cash Op Expenses        492409000000.0  525451000000.0  536154000000.0   \n",
       "     Daily Cash Op Expenses 1349065753.4247 1439591780.8219 1468915068.4932   \n",
       "     Defensive Interval              11.674         16.8499          15.685   \n",
       "\n",
       "                                       2023            2024            2025  \n",
       "AAPL WC / Net Income as %            -1.796        -24.9691             NaN  \n",
       "     Large Revenues                     1.0             1.0             0.0  \n",
       "     Quick Assets             91063000000.0   98581000000.0             NaN  \n",
       "     Cash Op Expenses        227550000000.0  225004000000.0             NaN  \n",
       "     Daily Cash Op Expenses  623424657.5342  616449315.0685             NaN  \n",
       "     Defensive Interval             146.069        159.9174             NaN  \n",
       "AMZN WC / Net Income as %           24.4339         19.3019             NaN  \n",
       "     Large Revenues                     1.0             1.0             0.0  \n",
       "     Quick Assets            139033000000.0  156653000000.0             NaN  \n",
       "     Cash Op Expenses        312262000000.0  328759000000.0             NaN  \n",
       "     Daily Cash Op Expenses  855512328.7671  900709589.0411             NaN  \n",
       "     Defensive Interval            162.5143        173.9218             NaN  \n",
       "META WC / Net Income as %          136.5927        106.5571             NaN  \n",
       "     Large Revenues                     1.0             1.0             0.0  \n",
       "     Quick Assets             81572000000.0   94809000000.0             NaN  \n",
       "     Cash Op Expenses         38490000000.0   35750000000.0             NaN  \n",
       "     Daily Cash Op Expenses  105452054.7945   97945205.4795             NaN  \n",
       "     Defensive Interval            773.5459          967.98             NaN  \n",
       "WMT  WC / Net Income as %         -141.6353       -100.1741        -88.1148  \n",
       "     Large Revenues                     1.0             1.0             1.0  \n",
       "     Quick Assets             16558000000.0   18663000000.0   19012000000.0  \n",
       "     Cash Op Expenses        579916000000.0  609260000000.0  638664000000.0  \n",
       "     Daily Cash Op Expenses 1588810958.9041 1669205479.4521 1749764383.5616  \n",
       "     Defensive Interval             10.4216         11.1808         10.8655  \n",
       "\n",
       "[24 rows x 21 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "custom_ratios = {\n",
    "    \"WC / Net Income as %\": \"(Working Capital / Net Income) * 100\",\n",
    "    \"Large Revenues\": \"Revenue > 1000000000\",\n",
    "    \"Quick Assets\": \"Cash and Short Term Investments + Accounts Receivable\",\n",
    "    \"Cash Op Expenses\": \"Cost of Goods Sold + Selling, General and Administrative Expenses \"\n",
    "    \"- Depreciation and Amortization\",\n",
    "    \"Daily Cash Op Expenses\": \"Cash Op Expenses / 365\",\n",
    "    \"Defensive Interval\": \"Quick Assets / Daily Cash Op Expenses\",\n",
    "}\n",
    "\n",
    "companies.ratios.collect_custom_ratios(custom_ratios_dict=custom_ratios)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4306cd49",
   "metadata": {},
   "source": [
    "It is also relatively straight forward to use the actual models provided you have the data available to flow through these functions. While the `Toolkit` class itself parses data from Financial Modeling Prep, if you utilize the individual models you can provide your own data as well while reaching the same results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c38bb4b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Asset Turnover</th>\n",
       "      <th>Quick Ratio</th>\n",
       "      <th>Return on Assets</th>\n",
       "      <th>Debt to Assets</th>\n",
       "      <th>Price to Earnings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.2</td>\n",
       "      <td>1.2307692307692308</td>\n",
       "      <td>0.5333333333333333</td>\n",
       "      <td>0.5</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.275</td>\n",
       "      <td>1.1666666666666667</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.7857142857142857</td>\n",
       "      <td>27.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.4</td>\n",
       "      <td>1.6363636363636365</td>\n",
       "      <td>0.13333333333333333</td>\n",
       "      <td>0.75</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.65</td>\n",
       "      <td>1.1333333333333333</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.8125</td>\n",
       "      <td>9.09090909090909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.8</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.26666666666666666</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Asset Turnover        Quick Ratio    Return on Assets      Debt to Assets  \\\n",
       "0             0.2 1.2307692307692308  0.5333333333333333                 0.5   \n",
       "1           0.275 1.1666666666666667                 0.2  0.7857142857142857   \n",
       "2             0.4 1.6363636363636365 0.13333333333333333                0.75   \n",
       "3            0.65 1.1333333333333333               0.075              0.8125   \n",
       "4             0.8                1.6                0.04 0.26666666666666666   \n",
       "\n",
       "   Price to Earnings  \n",
       "0               60.0  \n",
       "1               27.5  \n",
       "2              120.0  \n",
       "3   9.09090909090909  \n",
       "4               25.0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from financetoolkit.ratios import (\n",
    "    efficiency_model,\n",
    "    liquidity_model,\n",
    "    profitability_model,\n",
    "    solvency_model,\n",
    "    valuation_model,\n",
    ")\n",
    "\n",
    "# Note: this is dummy data, not actual data\n",
    "\n",
    "asset_turnover = efficiency_model.get_asset_turnover_ratio(\n",
    "    sales=pd.Series([100, 110, 120, 130, 80]),\n",
    "    average_total_assets=pd.Series([500, 400, 300, 200, 100]),\n",
    ")\n",
    "\n",
    "quick_ratio = liquidity_model.get_quick_ratio(\n",
    "    cash_and_equivalents=pd.Series([100, 110, 120, 130, 80]),\n",
    "    accounts_receivable=pd.Series([30, 20, 30, 20, 40]),\n",
    "    marketable_securities=pd.Series([30, 10, 30, 20, 40]),\n",
    "    current_liabilities=pd.Series([130, 120, 110, 150, 100]),\n",
    ")\n",
    "\n",
    "return_on_assets = profitability_model.get_return_on_assets(\n",
    "    net_income=pd.Series([80, 40, 40, 30, 20]),\n",
    "    average_total_assets=pd.Series([150, 200, 300, 400, 500]),\n",
    ")\n",
    "\n",
    "debt_to_assets = solvency_model.get_debt_to_assets_ratio(\n",
    "    total_debt=pd.Series([100, 110, 120, 130, 80]),\n",
    "    total_assets=pd.Series([200, 140, 160, 160, 300]),\n",
    ")\n",
    "\n",
    "price_to_earnings = valuation_model.get_price_to_earnings_ratio(\n",
    "    stock_price=pd.Series([30, 11, 12, 10, 30]),\n",
    "    earnings_per_share=pd.Series([0.5, 0.4, 0.1, 1.1, 1.2]),\n",
    ")\n",
    "\n",
    "components = {\n",
    "    \"Asset Turnover\": asset_turnover,\n",
    "    \"Quick Ratio\": quick_ratio,\n",
    "    \"Return on Assets\": return_on_assets,\n",
    "    \"Debt to Assets\": debt_to_assets,\n",
    "    \"Price to Earnings\": price_to_earnings,\n",
    "}\n",
    "\n",
    "\n",
    "pd.DataFrame(components)"
   ]
  }
 ],
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